Search results for: medical data visualization

Authors: Nir Nissim, Erez Shalom, Tomer Lancewiki, Yuval Elovici, Yuval Shahar

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Background: A Medical Device (MD) is an instrument, machine, implant, or similar device that includes a component intended for the purpose of the diagnosis, cure, treatment, or prevention of disease in humans or animals. Medical devices play increasingly important roles in health services eco-systems, including: (1) Patient Diagnostics and Monitoring; Medical Treatment and Surgery; and Patient Life Support Devices and Stabilizers. MDs are part of the medical device eco-system and are connected to the network, sending vital information to the internal medical information systems of medical centers that manage this data. Wireless components (e.g. Wi-Fi) are often embedded within medical devices, enabling doctors and technicians to control and configure them remotely. All these functionalities, roles, and uses of MDs make them attractive targets of cyber-attacks launched for many malicious goals; this trend is likely to significantly increase over the next several years, with increased awareness regarding MD vulnerabilities, the enhancement of potential attackers’ skills, and expanded use of medical devices. Significance: We propose to develop and implement Cyber-Med, a unique collaborative project of Ben-Gurion University of the Negev and the Clalit Health Services Health Maintenance Organization. Cyber-Med focuses on the development of a comprehensive detection framework that relies on a critical attack repository that we aim to create. Cyber-Med will allow researchers and companies to better understand the vulnerabilities and attacks associated with medical devices as well as providing a comprehensive platform for developing detection solutions. Methodology: The Cyber-Med detection framework will consist of two independent, but complementary detection approaches: one for known attacks, and the other for unknown attacks. These modules incorporate novel ideas and algorithms inspired by our team's domains of expertise, including cyber security, biomedical informatics, and advanced machine learning, and temporal data mining techniques. The establishment and maintenance of Cyber-Med’s up-to-date attack repository will strengthen the capabilities of Cyber-Med’s detection framework. Major Findings: Based on our initial survey, we have already found more than 15 types of vulnerabilities and possible attacks aimed at MDs and their eco-system. Many of these attacks target individual patients who use devices such pacemakers and insulin pumps. In addition, such attacks are also aimed at MDs that are widely used by medical centers such as MRIs, CTs, and dialysis engines; the information systems that store patient information; protocols such as DICOM; standards such as HL7; and medical information systems such as PACS. However, current detection tools, techniques, and solutions generally fail to detect both the known and unknown attacks launched against MDs. Very little research has been conducted in order to protect these devices from cyber-attacks, since most of the development and engineering efforts are aimed at the devices’ core medical functionality, the contribution to patients’ healthcare, and the business aspects associated with the medical device.

Keywords: medical device, cyber security, attack, detection, machine learning

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Authors: Elizabeta Krstić Vukelja

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Digitization of personal data is a consequence of the development of information and communication technologies that create a new work environment with many advantages and challenges, but also potential threats to privacy and personal data protection. Regulation (EU) 2016/679 of the European Parliament and of the Council is becoming a law and obligation that should address the issues of personal data protection and information security. The existence of the Regulation leads to the conclusion that national legislation in the field of virtual environment, protection of the rights of EU citizens and processing of their personal data is insufficiently effective. In the health system, special emphasis is placed on the processing of special categories of personal data, such as health data. The healthcare industry is recognized as a particularly sensitive area in which a large amount of medical data is processed, the digitization of which enables quick access and quick identification of the health insured. The protection of the individual requires quality IT solutions that guarantee the technical protection of personal categories. However, the real problems are the technical and human nature and the spatial limitations of the application of the Regulation. Some conclusions will be drawn by analyzing the implementation of the basic principles of the Regulation on the example of the Croatian health care system and comparing it with similar activities in other EU member states.

Keywords: regulation, healthcare system, personal dana protection, quality data assurance

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Authors: Jean Christian Ralaivao, Fabrice Razafindraibe, Hasina Rakotonirainy

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This document constitutes a resumption of work carried out in the field of complex data warehouses (DW) relating to the management and formalization of knowledge and metadata. It offers a methodological approach for integrating two concepts, knowledge and metadata, within the framework of a complex DW architecture. The objective of the work considers the use of the technique of knowledge representation by description logics and the extension of Common Warehouse Metamodel (CWM) specifications. This will lead to a fallout in terms of the performance of a complex DW. Three essential aspects of this work are expected, including the representation of knowledge in description logics and the declination of this knowledge into consistent UML diagrams while respecting or extending the CWM specifications and using XML as pivot. The field of application is large but will be adapted to systems with heteroge-neous, complex and unstructured content and moreover requiring a great (re)use of knowledge such as medical data warehouses.

Keywords: data warehouse, description logics, integration, knowledge, metadata

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Authors: Tassadit Issaadi Hamitouche, Nicolas Gillard, Jean Petit, Valerie Lavaste, Celine Mayousse

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Water is a fundamental resource for the industry. It is taken from the environment either from municipal distribution networks or from various natural water sources such as the sea, ocean, rivers, aquifers, etc. Once used, water is discharged into the environment, reprocessed at the plant or treatment plants. These withdrawals and discharges have a direct impact on natural water resources. These impacts can apply to the quantity of water available, the quality of the water used, or to impacts that are more complex to measure and less direct, such as the health of the population downstream from the watercourse, for example. Based on the analysis of data (meteorological, river characteristics, physicochemical substances), we wish to predict water stress episodes and anticipate prefectoral decrees, which can impact the performance of plants and propose improvement solutions, help industrialists in their choice of location for a new plant, visualize possible interactions between companies to optimize exchanges and encourage the pooling of water treatment solutions, and set up circular economies around the issue of water. The development of a system for the collection, processing, and use of data related to water resources requires the functional constraints specific to the latter to be made explicit. Thus the system will have to be able to store a large amount of data from sensors (which is the main type of data in plants and their environment). In addition, manufacturers need to have 'near-real-time' processing of information in order to be able to make the best decisions (to be rapidly notified of an event that would have a significant impact on water resources). Finally, the visualization of data must be adapted to its temporal and geographical dimensions. In this study, we set up an infrastructure centered on the TICK application stack (for Telegraf, InfluxDB, Chronograf, and Kapacitor), which is a set of loosely coupled but tightly integrated open source projects designed to manage huge amounts of time-stamped information. The software architecture is coupled with the cross-industry standard process for data mining (CRISP-DM) data mining methodology. The robust architecture and the methodology used have demonstrated their effectiveness on the study case of learning the level of a river with a 7-day horizon. The management of water and the activities within the plants -which depend on this resource- should be considerably improved thanks, on the one hand, to the learning that allows the anticipation of periods of water stress, and on the other hand, to the information system that is able to warn decision-makers with alerts created from the formalization of prefectoral decrees.

Keywords: data mining, industry, machine Learning, shortage, water resources

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Authors: Roni Ramon-Gonen, Amir Dori, Shahar Shelly

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Background and objectives: Healthcare professionals produce abundant textual information in their daily clinical practice. The extraction of insights from all the gathered information, mainly unstructured and lacking in normalization, is one of the major challenges in computational medicine. In this respect, text mining assembles different techniques to derive valuable insights from unstructured textual data, so it has led to being especially relevant in Medicine. Neurological patient’s history allows the clinician to define the patient’s symptoms and along with the result of the nerve conduction study (NCS) and electromyography (EMG) test, assists in formulating a differential diagnosis. Past medical history (PMH) helps to direct the latter. In this study, we aimed to identify relevant PMH, understand which PMHs are common among patients in the referral cohort and documented by the medical staff, and examine the differences by sex and age in a large cohort based on textual format notes. Methods: We retrospectively identified all patients with abnormal NCS between May 2016 to February 2022. Age, gender, and all NCS attributes reports were recorded, including the summary text. All patients’ histories were extracted from the text report by a query. Basic text cleansing and data preparation were performed, as well as lemmatization. Very popular words (like ‘left’ and ‘right’) were deleted. Several words were replaced with their abbreviations. A bag of words approach was used to perform the analyses. Different visualizations which are common in text analysis, were created to easily grasp the results. Results: We identified 5282 unique patients. Three thousand and five (57%) patients had documented PMH. Of which 60.4% (n=1817) were males. The total median age was 62 years (range 0.12 – 97.2 years), and the majority of patients (83%) presented after the age of forty years. The top two documented medical histories were diabetes mellitus (DM) and surgery. DM was observed in 16.3% of the patients, and surgery at 15.4%. Other frequent patient histories (among the top 20) were fracture, cancer (ca), motor vehicle accident (MVA), leg, lumbar, discopathy, back and carpal tunnel release (CTR). When separating the data by sex, we can see that DM and MVA are more frequent among males, while cancer and CTR are less frequent. On the other hand, the top medical history in females was surgery and, after that, DM. Other frequent histories among females are breast cancer, fractures, and CTR. In the younger population (ages 18 to 26), the frequent PMH were surgery, fractures, trauma, and MVA. Discussion: By applying text mining approaches to unstructured data, we were able to better understand which medical histories are more relevant in these circumstances and, in addition, gain additional insights regarding sex and age differences. These insights might help to collect epidemiological demographical data as well as raise new hypotheses. One limitation of this work is that each clinician might use different words or abbreviations to describe the same condition, and therefore using a coding system can be beneficial.

Keywords: abnormal studies, healthcare analytics, medical history, nerve conduction studies, text mining, textual analysis

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Authors: Elzbieta Sikorska-Simmons

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Advanced dementia is a progressive terminal brain disease that is accompanied by a syndrome of difficult to manage symptoms and complications that eventually lead to death. The management of advanced dementia poses major challenges to family caregivers who act as patient health care proxies in making medical treatment decisions. Little is known, however, about how they manage advanced dementia and how their treatment choices influence the quality of patient life. This prospective qualitative study examines the key medical treatment decisions that family caregivers make while managing advanced dementia. The term ‘family caregiver’ refers to a relative or a friend who is primarily responsible for managing patient’s medical care needs and legally authorized to give informed consent for medical treatments. Medical decision-making implies a process of choosing between treatment options in response to patient’s medical care needs (e.g., worsening comorbid conditions, pain, infections, acute medical events). Family caregivers engage in this process when they actively seek treatments or follow recommendations by healthcare professionals. Better understanding of medical decision-making from the family caregiver perspective is needed to design interventions that maximize the quality of patient life and limit inappropriate treatments. Data were collected in three waves of semi-structured interviews with 20 family caregivers for patients with advanced dementia. A purposive sample of 20 family caregivers was recruited from a senior care center in Central Florida. The qualitative personal interviews were conducted by the author in 4-5 months intervals. The ethical approval for the study was obtained prior to the data collection. Advanced dementia was operationalized as stage five or higher on the Global Deterioration Scale (GDS) (i.e., starting with the GDS score of five, patients are no longer able survive without assistance due to major cognitive and functional impairments). Information about patients’ GDS scores was obtained from the Center’s Medical Director, who had an in-depth knowledge of each patient’s health and medical treatment history. All interviews were audiotaped and transcribed verbatim. The qualitative data analysis was conducted to answer the following research questions: 1) what treatment decisions do family caregivers make while managing the symptoms of advanced dementia and 2) how do these treatment decisions influence the quality of patient life? To validate the results, the author asked each participating family caregiver if the summarized findings accurately captured his/her experiences. The identified medical decisions ranged from seeking specialist medical care to end-of-life care. The most common decisions were related to arranging medical appointments, medication management, seeking treatments for pain and other symptoms, nursing home placement, and accessing community-based healthcare services. The most challenging and consequential decisions were related to the management of acute complications, hospitalizations, and discontinuation of treatments. Decisions that had the greatest impact on the quality of patient life and survival were triggered by traumatic falls, worsening psychiatric symptoms, and aspiration pneumonia. The study findings have important implications for geriatric nurses in the context of patient/caregiver-centered dementia care. Innovative nursing approaches are needed to support family caregivers to effectively manage medical care needs of patients with advanced dementia.

Keywords: advanced dementia, family caregiver, medical decision-making, symptom management

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Authors: Ronald Blough

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Hospitals, clinics, and medical facilities are the core of the Health Services sector providing 24/7 medical care to those in need. Any disruption of these important medical services highlights the vulnerabilities in the medical system. An internal or external event can create a catastrophic incident paralyzing the medical services causing the facility to shift into emergency operations with the possibility of evacuation. The hospital administrator and government officials must decide in a very short amount of time whether to shelter in place or evacuate. This presentation will identify best practice recommendations regarding the hospital evacuation decision and response analyzing previous hospital evacuations to encourage hospitals in the region to review or develop their own emergency evacuation plans.

Keywords: disaster preparedness, hospital evacuation, shelter-in-place, incident containment, health services vulnerability, hospital resources

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Authors: Yu-Chuan Huang

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Introduction: There is a higher mortality rate for unplanned transfer to intensive care units. It also needs a longer length of stay and makes the intensive care unit beds cannot be effectively used. It affects the immediate medical treatment of critically ill patients, resulting in a drop in the quality of medical care. Purpose: The purpose of this study was using SOFA and APACHEII score to analyze the mortality rate of the cases transferred from ED to ICU. According to the score that should be provide an appropriate care as early as possible. Methods: This study was a descriptive experimental design. The sample size was estimated at 220 to reach a power of 0.8 for detecting a medium effect size of 0.30, with a 0.05 significance level, using G-power. Considering an estimated follow-up loss, the required sample size was estimated as 242 participants. Data were calculated by medical system of SOFA and APACHEII score that cases transferred from ED to ICU in 2016. Results: There were 233 participants meet the study. The medical records showed 33 participants’ mortality. Age and sex with QSOFA , SOFA and sex with APACHEII showed p>0.05. Age with APCHHII in ED and ICU showed r=0.150, 0,268 (p < 0.001**). The score with mortality risk showed: ED QSOFA is r=0.235 (p < 0.001**), exp(B)=1.685(p = 0.007); ICU SOFA 0.78 (p < 0.001**), exp(B)=1.205(p < 0.001). APACHII in ED and ICU showed r= 0.253, 0.286 (p < 0.001**), exp(B) = 1.041,1.073(p = 0.017,0.001). For SOFA, a cutoff score of above 15 points was identified as a predictor of the 95% mortality risk. Conclusions: The SOFA and APACHE II were calculated based on initial laboratory data in the Emergency Department, and during the first 24 hours of ICU admission. In conclusion, the SOFA and APACHII score is significantly associated with mortality and strongly predicting mortality. Early predictors of morbidity and mortality, which we can according the predicting score, and provide patients with a detail assessment and proper care, thereby reducing mortality and length of stay.

Keywords: SOFA, APACHEII, mortality, ICU

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Authors: Faisal Kalota

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Big Data and analytics have gained a huge momentum in recent years. Big Data feeds into the field of Learning Analytics (LA) that may allow academic institutions to better understand the learners’ needs and proactively address them. Hence, it is important to have an understanding of Big Data and its applications. The purpose of this descriptive paper is to provide an overview of Big Data, the technologies used in Big Data, and some of the applications of Big Data in education. Additionally, it discusses some of the concerns related to Big Data and current research trends. While Big Data can provide big benefits, it is important that institutions understand their own needs, infrastructure, resources, and limitation before jumping on the Big Data bandwagon.

Keywords: big data, learning analytics, analytics, big data in education, Hadoop

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Authors: Rafaella Nogaroli

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It is presented hypothetical cases in the context of AI algorithms to support clinical decisions, in order to discuss the importance of doctors to respect AI ethical principles. Regarding the principle of transparency and explanation, there is an impact on the new model of patient consent and on the understanding of qualified information. Besides, the human control of technology (AI as a tool) should guide the physician's activity; otherwise, he breaks the patient's legitimate expectation in a specific result, with the consequent transformation of the medical obligation nature.

Keywords: medical law, artificial intelligence, ethical principles, patient´s informed consent, medical obligations

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Authors: Orawan Vichiansan, J. Kraipoj, K.Phandech, P. Sirasaporn

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Generally, frozen shoulder will improve over time, although it may take a long time up to year. The symptoms of frozen shoulder present by pain around shoulder and consequently limit range of motions. The effect of frozen shoulder leads to limit activities daily living life and high medical care cost. Physiotherapy is well known treatment for frozen shoulder but there was no data about the treatment of physiotherapy in frozen shoulder and length of follow up. Thus the aim of this study was to investigate physiotherapy program for frozen shoulder on range of motion and length of follow up. A retrospective study design was conducted. 469 medical records of patients with frozen shoulder were reviewed. These frozen shoulders were treated at physiotherapy unit, department of Rehabilitation last 3 years (January, 2014- December, 2016). The data consist of range of motions and length of follow up was recorded. The medical record of 183 males and 286 females with average aged 57.82±12.32 years were reviewed in this study. There was a statistically significant increase in shoulder flexion [mean difference 30.24 with 95%CI were [24.37-36.12], shoulder abduction [mean difference 34.93 with 95%CI were 27.8-42.0], shoulder internal rotation [mean difference 17.25 with 95%CI were 12.55-21.95] and shoulder external rotation [mean difference 17.71 with 95%CI were [13.07-22.36] respectively. In addition, the length of follow up averaged 84 days. In summary, the retrospective study show physiotherapy program likely to be benefit for patients with frozen shoulder in term of range of motion and short length of follow up.

Keywords: frozen shoulder, physiotherapy, range of motions, length of follow up

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Authors: Scott A. Ochsner, Christopher M. Watkins, Apollo McOwiti, David L. Steffen Lauren B. Becnel, Neil J. McKenna

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Understanding signaling by nuclear receptors (NRs) requires an appreciation of their cognate ligand- and tissue-specific transcriptomes. While target gene regulation data are abundant in this field, they reside in hundreds of discrete publications in formats refractory to routine query and analysis and, accordingly, their full value to the NR signaling community has not been realized. One of the mandates of the Nuclear Receptor Signaling Atlas (NURSA) is to facilitate access of the community to existing public datasets. Pursuant to this mandate we are developing a freely-accessible community web resource, Transcriptomine, to bring together the sum total of available expression array and RNA-Seq data points generated by the field in a single location. Transcriptomine currently contains over 25,000,000 gene fold change datapoints from over 1200 contrasts relevant to over 100 NRs, ligands and coregulators in over 200 tissues and cell lines. Transcriptomine is designed to accommodate a spectrum of end users ranging from the bench researcher to those with advanced bioinformatic training. Visualization tools allow users to build custom charts to compare and contrast patterns of gene regulation across different tissues and in response to different ligands. Our resource affords an entirely new paradigm for leveraging gene expression data in the NR signaling field, empowering users to query gene fold changes across diverse regulatory molecules, tissues and cell lines, target genes, biological functions and disease associations, and that would otherwise be prohibitive in terms of time and effort. Transcriptomine will be regularly updated with gene lists from future genome-wide expression array and expression-sequencing datasets in the NR signaling field.

Keywords: target gene database, informatics, gene expression, transcriptomics

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Authors: Raffaele Danilo Esposito, Domingo Planes Meseguer, Maria Del Pilar Dorado Rodriguez

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As far as we know, it is still unavailable a commercial solution which would allow to manage, openly and configurable up to user needs, the huge amount of data generated in a modern Radiation Oncology Department. Currently, available information management systems are mainly focused on Record & Verify and clinical data, and only to a small extent on physical data. Thus, results in a partial and limited use of the actually available information. In the present work we describe the implementation at our department of a centralized information management system based on a web server. Our system manages both information generated during patient planning and treatment, and information of general interest for the whole department (i.e. treatment protocols, quality assurance protocols etc.). Our objective it to be able to analyze in a simple and efficient way all the available data and thus to obtain quantitative evaluations of our treatments. This would allow us to improve our work flow and protocols. To this end we have implemented a relational data base which would allow us to use in a practical and efficient way all the available information. As always we only use license free software.

Keywords: information management system, radiation oncology, medical physics, free software

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Authors: Nasrudin Andi Mappaware, Muh. Wirawan Harahap, Erlin Syahril, Farah Ekawati Mulyadi

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The increasing trend of cesarean sections, especially those performed on self-request without medical indications, presents complex dilemmas related to medical aspects, professionalism, and bioethics. This study aims to investigate the medical, professional, and bioethical considerations surrounding anesthesia in cesarean sections performed on self-request without medical indications. We report the case of a 27-year-old woman, G1P0A0 gravid 38 weeks, admitted to the hospital for a planned cesarean section on request for the reason that she could not tolerate pain and requested on a date that corresponded to the date and month of her mother's birth. Cesarean section on patient request fulfills the principle of autonomy, which states that patients have the right to themselves. However, this medical procedure is still considered no safer and riskier even though medical technology has developed rapidly. Furthermore, anesthesia during cesarean section at self-request without medical indications is a dilemma for anesthesiologists considering the risks and complications of anesthesia for both the fetus and the mother. The trend in increasing the number of cesarean sections is influenced by patient reasons such as not being able to tolerate pain, trust factors, and worry about damage to the birth canal.

Keywords: anesthesia, bioethics, cesarean section, self-request, professionalism

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Authors: Hannah Yael Ephraim

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During reproductive age (between 15 and 44), women are particularly susceptible to psychiatric illness. Depression and anxiety disorders are especially common for women during reproductive age. Women of reproductive age are also at greater risk for multiple physical conditions during this time. Existing literature focuses on the impact of mental health on physical health, showing that people with anxiety and depression repeatedly show greater physical health risk among those with developing chronic medical illness. However, there is limited research on the impact physical health has on mental health in women of reproductive age, a large and vulnerable population. For this reason, the current study seeks to ask the following questions: are women of reproductive age with a diagnosis of a chronic physical condition more likely to experience symptoms of mental illness than women without a diagnosis of a chronic physical condition? Does the type of physical illness relate to signs and symptoms of depression and anxiety? A quasi-experimental research design was implemented to compare the mental health outcomes of women with the diagnosis of chronic medical conditions and women without the diagnosis of a chronic medical condition. Quantitative data was collected through an anonymous ten-minute Qualtrics survey. The survey was sent out through multiple online platforms. The sample includes two groups of women: one group with the diagnosis of a chronic medical illness, and one group without a diagnosis and/or symptoms (N = 541). Participants identify as a woman and are between the ages of 15 and 44. A comparison of women with a diagnosis of a chronic physical condition and those without a diagnosis will be conducted to explore differences in depression and anxiety symptoms between women with and without a chronic medical diagnosis. The impact race, SES, and occupation will also be addressed in relation to anxiety and/or depression in women of reproductive age. This study will further the understanding of the relationship between mental illness in women of reproductive age with chronic medical conditions. The results of this study will have implications for the integration of mental health care in women’s health centers and perhaps training of clinicians and physicians providing psychological and medical care to women of reproductive age.

Keywords: mental health, physical health, reproductive age, women

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Authors: Linyao Qiu, Zhiqiang Du

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As the rapid development of urbanization, economic developments, and steady population growth in China, the widespread devastation, economic damages, and loss of human lives caused by numerous forms of natural disasters are becoming increasingly serious every year. Disaster management requires available and effective cooperation of different roles and organizations in whole process including mitigation, preparedness, response and recovery. Due to the imbalance of regional development in China, the disaster management capabilities of national and provincial disaster reduction centers are uneven. When an undeveloped area suffers from disaster, neither local reduction department could get first-hand information like high-resolution remote sensing images from satellites and aircrafts independently, nor sharing mechanism is provided for the department to access to data resources deployed in other place directly. Most existing disaster management systems operate in a typical passive data-centric mode and work for single department, where resources cannot be fully shared. The impediment blocks local department and group from quick emergency response and decision-making. In this paper, we introduce a collaborative platform for distributed disaster reduction. To address the issues of imbalance of sharing data sources and technology in the process of disaster reduction, we propose a multi-role oriented collaboration business mechanism, which is capable of scheduling and allocating for optimum utilization of multiple resources, to link various roles for collaborative reduction business in different place. The platform fully considers the difference of equipment conditions in different provinces and provide several service modes to satisfy technology need in disaster reduction. An integrated collaboration system based on focusing services mechanism is designed and implemented for resource scheduling, functional integration, data processing, task management, collaborative mapping, and visualization. Actual applications illustrate that the platform can well support data sharing and business collaboration between national and provincial department. It could significantly improve the capability of disaster reduction in China.

Keywords: business collaboration, data sharing, distributed disaster reduction, focusing service

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Authors: M. Sandhya, R. M. Madhumitha, Sharmila Sankar

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Interoperable medical devices (IMDs) face threats due to the increased attack surface accessible by interoperability and the corresponding infrastructure. Initiating networking and coordination functionalities primarily modify medical systems' security properties. Understanding the threats is a vital first step in ultimately crafting security solutions for such systems. The key to this problem is coming up with some common types of threats or attacks with those of security and privacy, and providing this information as a roadmap. This paper analyses the security issues in interoperability of devices and presents the main types of threats that have to be considered to build a secured system.

Keywords: interoperability, threats, attacks, medical devices

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Authors: Yasuyuki Takahashi, Hayato Ishimura, Masao Miyagawa, Teruhito Mochizuki

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Quantitative measurement of myocardium perfusion is possible with single photon emission computed tomography (SPECT) using a semiconductor detector. However, accumulation of ^99mTc-tetrofosmin in the liver may make it difficult to assess that accurately in the inferior myocardium. Our idea is to reduce the high accumulation in the liver by using dynamic SPECT imaging and a technique called time subtraction. We evaluated the performance of a new SPECT system with a cadmium-zinc-telluride solid-state semi- conductor detector (Discovery NM 530c; GE Healthcare). Our system acquired list-mode raw data over 10 minutes for a typical patient. From the data, ten SPECT images were reconstructed, one for every minute of acquired data. Reconstruction with the semiconductor detector was based on an implementation of a 3-D iterative Bayesian reconstruction algorithm. We studied 20 patients with coronary artery disease (mean age 75.4 ± 12.1 years; range 42-86; 16 males and 4 females). In each subject, 259 MBq of ^99mTc-tetrofosmin was injected intravenously. We performed both a phantom and a clinical study using dynamic SPECT. An approximation to a liver-only image is obtained by reconstructing an image from the early projections during which time the liver accumulation dominates (0.5~2.5 minutes SPECT image-5~10 minutes SPECT image). The extracted liver-only image is then subtracted from a later SPECT image that shows both the liver and the myocardial uptake (5~10 minutes SPECT image-liver-only image). The time subtraction of liver was possible in both a phantom and the clinical study. The visualization of the inferior myocardium was improved. In past reports, higher accumulation in the myocardium due to the overlap of the liver is un-diagnosable. Using our time subtraction method, the image quality of the ^99mTc-tetorofosmin myocardial SPECT image is considerably improved.

Keywords: 99mTc-tetrofosmin, dynamic SPECT, time subtraction, semiconductor detector

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Authors: Roman Klas, František Pochylý, Pavel Rudolf

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This paper is focused on the CFD simulation of the radiaxial pump (i.e. mixed flow pump) with the aim to detect the reasons of Y-Q characteristic instability. The main reasons of pressure pulsations were detected by means of the analysis of velocity and pressure fields within the pump combined with the theoretical approach. Consequently, the modifications of spiral case and pump suction area were made based on the knowledge of flow conditions and the shape of dissipation function. The primary design of pump geometry was created as the base model serving for the comparison of individual modification influences. The basic experimental data are available for this geometry. This approach replaced the more complicated and with respect to convergence of all computational tasks more difficult calculation for the compressible liquid flow. The modification of primary pump consisted in inserting the three fins types. Subsequently, the evaluation of pressure pulsations, specific energy curves and visualization of velocity fields were chosen as the criterion for successful design.

Keywords: CFD, radiaxial pump, spiral case, stability

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Authors: David Percy

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Landslides are a geologic phenomenon that affects a large number of inhabited places and are constantly being monitored and studied for the prediction of future occurrences. Reconstructability analysis (RA) is a methodology for extracting informative models from large volumes of data that work exclusively with discrete data. While RA has been used in medical applications and social science extensively, we are introducing it to the spatial sciences through applications like landslide prediction. Since RA works exclusively with discrete data, such as soil classification or bedrock type, working with continuous data, such as porosity, requires that these data are binned for inclusion in the model. RA constructs models of the data which pick out the most informative elements, independent variables (IVs), from each layer that predict the dependent variable (DV), landslide occurrence. Each layer included in the model retains its classification data as a primary encoding of the data. Unlike other machine learning algorithms that force the data into one-hot encoding type of schemes, RA works directly with the data as it is encoded, with the exception of continuous data, which must be binned. The usual physical and derived layers are included in the model, and testing our results against other published methodologies, such as neural networks, yields accuracy that is similar but with the advantage of a completely transparent model. The results of an RA session with a data set are a report on every combination of variables and their probability of landslide events occurring. In this way, every combination of informative state combinations can be examined.

Keywords: reconstructability analysis, machine learning, landslides, raster analysis

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Authors: Goitom Molalign Takele, Tsegalem Hailemariam Ballo, Kiros Belay Gebrekidan, Birhan Gebresilassie Gebregiorgis

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Background: Emergency medical services (EMS) are services that provide out-of-hospital emergency medical care to injured or ill peoples, and transporting to definitive care. EMS is an integral part of the emergency medical system and has been associated with decreased morbidity and mortality related to emergency cases. The aim of this study was to assess the utilization, barriers, and determinants of EMS in Mekelle, Ethiopia. Methods: A community-based cross-sectional study was conducted in selected sub-cities of Mekelle. A multistage sampling method was employed to recruit study participants, and data were collected by trained data collectors using an interviewer-administered questionnaire. Multivariate logistic regression analysis was used to examine the statistical association of the determinants of EMS utilization. Results: Half (50.5%) of the respondents had experienced or witnessed an emergency incident in the past year. The common means of transportations used were Bajaj’s (39.2%) and ambulances (22.7%). Majority (88.1%) of the respondents did not knew the EMS access phone number of an ambulance. As their preferred mode of transportation in case of emergency conditions, 42.2% of the participants reported an ambulance, followed by Bajaj 33.7%. Where participants who had gynecologic emergencies were 9.4 times (AOR=9.4, 95% CI: 1.04, 85, p=0.046), and those who knew any ambulance numbers were 3.6 times (AOR=3.6, 95% CI: 1.22, 10.8, p=0.02) more likely to use ambulance services in case of emergencies. Conclusion: The ambulance utilization level in Mekelle city was low and victims of emergency conditions were being transported mainly using public transports such as Bajaj’s and taxis. Even though the perception of the public towards EMS services is favorable, lack of awareness of EMS access, and lack of integrated EMS system in the city are the barriers that may have contributed to the low utilization. Actions to improve EMS access and integrating the system are warranted to promote the services utilization.

Keywords: emergency medical services, utilization, Mekelle, barriers

Procedia PDF Downloads 78

Authors: Supunmali Ahangama, Danny Chiang Choon Poo

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Health analytics (HA) is used in healthcare systems for effective decision-making, management, and planning of healthcare and related activities. However, user resistance, the unique position of medical data content, and structure (including heterogeneous and unstructured data) and impromptu HA projects have held up the progress in HA applications. Notably, the accuracy of outcomes depends on the skills and the domain knowledge of the data analyst working on the healthcare data. The success of HA depends on having a sound process model, effective project management and availability of supporting tools. Thus, to overcome these challenges through an effective process model, we propose an HA process model with features from the rational unified process (RUP) model and agile methodology.

Keywords: agile methodology, health analytics, unified process model, UML

Procedia PDF Downloads 507

Authors: Laleh Boroumand, Muhammad Shiraz, Abdullah Gani, Rashid Hafeez Khokhar

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Cloud computing being the use of hardware and software that are delivered as a service over a network has its application in the area of health care. Due to the emergency cases reported in most of the medical centers, prompt for an efficient scheme to make health data available with less response time. To this end, we propose a mobile global healthcare village (MGHV) model that combines the components of three deployment model which include country, continent and global health cloud to help in solving the problem mentioned above. In the creation of continent model, two (2) data centers are created of which one is local and the other is global. The local replay the request of residence within the continent, whereas the global replay the requirements of others. With the methods adopted, there is an assurance of the availability of relevant medical data to patients, specialists, and emergency staffs regardless of locations and time. From our intensive experiment using the simulation approach, it was observed that, broker policy scheme with respect to optimized response time, yields a very good performance in terms of reduction in response time. Though, our results are comparable to others when there is an increase in the number of virtual machines (80-640 virtual machines). The proportionality in increase of response time is within 9%. The results gotten from our simulation experiments shows that utilizing MGHV leads to the reduction of health care expenditures and helps in solving the problems of unqualified medical staffs faced by both developed and developing countries.

Keywords: cloud computing (MCC), e-healthcare, availability, response time, service broker policy

Procedia PDF Downloads 377

Authors: Zainab Idrees Ahmad, Mahjabeen Qureshi, Zainab Hussain

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Standard precautions are a set of infection control practices used to prevent the transmission of diseases that can be acquired by contact with body fluids, non-intact skin, and mucous membranes. Lack of practice of SPs can result in a considerable increase in morbidity and mortality rates. Medical students (the future physicians) should have the highest knowledge of standard precautions to prevent the spread of nosocomial infections and ensure their safety as well. This study was designed. To assess the knowledge of medical students regarding standard precautions. And explore the attitude of medical students of MBBS in the third, fourth and final year towards standard precautions.: A descriptive cross-sectional study was conducted in the setting of Rawalpindi Medical University, Pakistan including the students of MBBS in their 3rd, 4th and final years. The study duration was from October 2022 to February 2023. The sample size calculated was 282 with a confidence interval of 95%. A questionnaire was structured utilizing the WHO guidelines on SPs assessing knowledge and attitude regarding hand hygiene, needle stick injury, use of gloves and mask, and sharp disposal. A total of 300 responses were received utilizing the technique of non-random convenience sampling. Data was analyzed using the latest version of SPSS.:Knowledge score regarding components of SPs, hand hygiene, and moments of hand hygiene was satisfactory. However, score regarding the use of PPE, needle stick injury, and sharp disposal was low. Almost all the students were compliant with the proper washing of hands but the observation of recommended time length was lacking. Compliance with the use of correct PPE and informing the supervisor upon getting a needle stick injury was low. This study signifies that medical students lack knowledge regarding standard precautions. This is alarming as this can be the vehicle for the spread of nosocomial infections. Proper training should be given to medical students to prevent the spread of hospital-acquired infections.

Keywords: attitude, knowledge, medical students, standard precautions

Procedia PDF Downloads 127

Authors: Shujon Mohammed Alazzam, Sarah Saad Alamer, Omar Hassan Kasule, Lama Suliman Aleid, Mohammad Abdulaziz Alakeel, Boshra Mosleh Alanazi, Abdullah Abdulelah Altowairqi, Yahya Ali Al-Asiri

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Background: Interventional radiology (IR) is a specialized field within radiology that diagnose and treat several conditions through a minimally invasive surgical procedure that involves the use of various radiological techniques. In the last few years, the role of IR has expanded to include a variety of organ systems which have been led to an increase in demand for these Specialties. The level of knowledge regarding IR is relatively low in general. In this study, we aimed to investigate the perceptions of interventional radiology (IR) as a specialty among medical students and medical interns in Riyadh, Saudi Arabia. Methodology: This study was a cross section. The target population is medical students in January 2023 in Riyadh city, KSA. We used the questionnaire for face-to-face interviews with voluntary participants to assess their knowledge of Interventional radiology. Permission was taken from participants to use their information. Assuring them that the data in this study was used only for scientific purposes. Results: According to the inclusion criteria, a total of 314 students participated in the study. (49%) of the participants were in the preclinical years, and (51%) were in the clinical years. The findings indicate more than half of the students think that they had good information about IR (58%), while (42%) reported that they had poor information and knowledge about IR. Only (28%) of students were planning to take an elective and radiology rotation, (and 27%) said they would consider a career in IR. (73%) of the participants who would not consider a career in IR, the highest reasons in order were due to "I do not find it interesting" (45%), then "Radiation exposure" (14%). Around half (48%) thought that an IRs must complete a residency training program in both radiology and surgery, and just (36%) of the students believe that an IRs must finish training in radiology. Our data show the procedures performed by IRs that (66%) lower limb angioplasty and stenting (58%) Cardiac angioplasty or stenting. (68%) of the students were familiar with angioplasty. When asked about the source of exposure to angioplasty, the majority (46%) were from a cardiologist, (and 16%) were from the interventional radiologist. Regarding IR career prospects, (78%) of the students believe that IRs have good career prospects. In conclusion, our findings reveal that the perception and exposure to IR among medical students and interns are generally poor. This has a direct influence on the student's decision regarding IR as a career path. Recommendations to attract medical students and promote IR as a career should be increased knowledge among medical students and future physicians through early exposure to IR, and this will promote the specialty's growth; also, involvement of the Saudi Interventional Radiology Society and Radiological Society of Saudi Arabia is essential.

Keywords: knowledge, medical students, perceptions, radiology, interventional radiology, Saudi Arabia

Procedia PDF Downloads 91

Authors: Mehrdad Shafiei Dizaji, Hoda Azari

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The research explores the pioneering integration of Physics-Informed Neural Networks (PINNs) into the domain of Ground-Penetrating Radar (GPR) data prediction, akin to advancements in medical imaging for tracking tumor progression in the human body. This research presents a detailed development framework for a specialized PINN model proficient at interpreting and forecasting GPR data, much like how medical imaging models predict tumor behavior. By harnessing the synergy between deep learning algorithms and the physical laws governing subsurface structures—or, in medical terms, human tissues—the model effectively embeds the physics of electromagnetic wave propagation into its architecture. This ensures that predictions not only align with fundamental physical principles but also mirror the precision needed in medical diagnostics for detecting and monitoring tumors. The suggested deep learning structure comprises three components: a CNN, a spatial feature channel attention (SFCA) mechanism, and ConvLSTM, along with temporal feature frame attention (TFFA) modules. The attention mechanism computes channel attention and temporal attention weights using self-adaptation, thereby fine-tuning the visual and temporal feature responses to extract the most pertinent and significant visual and temporal features. By integrating physics directly into the neural network, our model has shown enhanced accuracy in forecasting GPR data. This improvement is vital for conducting effective assessments of bridge deck conditions and other evaluations related to civil infrastructure. The use of Physics-Informed Neural Networks (PINNs) has demonstrated the potential to transform the field of Non-Destructive Evaluation (NDE) by enhancing the precision of infrastructure deterioration predictions. Moreover, it offers a deeper insight into the fundamental mechanisms of deterioration, viewed through the prism of physics-based models.

Keywords: physics-informed neural networks, deep learning, ground-penetrating radar (GPR), NDE, ConvLSTM, physics, data driven

Procedia PDF Downloads 43

Authors: Palash Dutta

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More frequently uncertainties are encountered in medical diagnosis and therefore it is the most important and interesting area of applications of fuzzy set theory. In this present study, an attempt has been made to extend Sanchez’s approach for medical diagnosis via interval valued picture fuzzy sets and exhibit the technique with suitable case studies. In this article, it is observed that a refusal can be expressed in the databases concerning the examined objects. The technique is performing diagnosis on the basis of distance measures and as a result, this approach makes it possible to introduce weights of all symptoms and consequently patient can be diagnosed directly.

Keywords: medical diagnosis, uncertainty, fuzzy set, picture fuzzy set, interval valued picture fuzzy set

Procedia PDF Downloads 385

Authors: Zhuang Yiwen

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The paper examines the challenges facing the Singapore healthcare system related to the tracking and traceability of medical devices. One of the major challenges identified is the lack of a standard coding system for medical devices, which makes it difficult to track them effectively. The paper suggests the use of the Unique Device Identifier (UDI) as a single standard for medical devices to improve tracking and reduce errors. The paper also explores the use of barcoding and image recognition to identify and document medical devices in nursing practices. In nursing practices, the use of barcodes for identifying medical devices is common. However, the information contained in these barcodes is often inconsistent, making it challenging to identify which segment contains the model identifier. Moreover, the use of barcodes may be improved with the use of UDI, but many subsidized accessories may still lack barcodes. The paper suggests that the readiness for UDI and barcode standardization requires standardized information, fields, and logic in electronic medical record (EMR), operating theatre (OT), and billing systems, as well as barcode scanners that can read various formats and selectively parse barcode segments. Nursing workflow and data flow also need to be taken into account. The paper also explores the use of image recognition, specifically the Tesseract OCR engine, to identify and document implants in public hospitals due to limitations in barcode scanning. The study found that the solution requires an implant information database and checking output against the database. The solution also requires customization of the algorithm, cropping out objects affecting text recognition, and applying adjustments. The solution requires additional resources and costs for a mobile/hardware device, which may pose space constraints and require maintenance of sterile criteria. The integration with EMR is also necessary, and the solution require changes in the user's workflow. The paper suggests that the long-term use of Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) as a supporting terminology to improve clinical documentation and data exchange in healthcare. SNOMED CT provides a standardized way of documenting and sharing clinical information with respect to procedure, patient and device documentation, which can facilitate interoperability and data exchange. In conclusion, the paper highlights the challenges facing the Singapore healthcare system related to the tracking and traceability of medical devices. The paper suggests the use of UDI and barcode standardization to improve tracking and reduce errors. It also explores the use of image recognition to identify and document medical devices in nursing practices. The paper emphasizes the importance of standardized information, fields, and logic in EMR, OT, and billing systems, as well as barcode scanners that can read various formats and selectively parse barcode segments. These recommendations could help the Singapore healthcare system to improve tracking and traceability of medical devices and ultimately enhance patient safety.

Keywords: medical device tracking, unique device identifier, barcoding and image recognition, systematized nomenclature of medicine clinical terms

Procedia PDF Downloads 79

Authors: Catherine Bernard

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The maldistribution of clinicians within countries is well documented. It is a common theme throughout the world that rural areas often struggle to recruit and retain health workers resulting in inadequate healthcare for many. This paper will concentrate on the responsibilities that medical schools may have in addressing this shortage of rural health workers. Recommendations are made with regards to targeted rural student admissions, rurally-based medical schools, rural clinical rotations and a curriculum orientated towards rural health issues. The evidence gathered suggests that individual factors are positive in encouraging health workers to practice in rural locations. However, there is strength in numbers, and combining all the recommendations will likely result in a synergistic effect, thereby increasing numbers of rural health workers and achieving accessible healthcare for those living in rural populations.

Keywords: medical education, medical education design, public health, rural health

Procedia PDF Downloads 268

Authors: Vega Erdiana Dwi Fransiska, Abyan Rai Fauzan Machmudin

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Particularly, space configuration zoning is the very first juncture of a complete space configuration and region planning. Zoning is aimed to define discrete knowledge based on a local wisdom. Ancient predecessor scientifically study the sign of natural disaster towards ethnography approach by operating this knowledge. There are three main functions of space zoning, which are control function, guidance function, and additional function. The control function refers to an instrument for development control and as one of the essentials in controlling land use. Hence, the guidance function indicates as guidance for proposing operational planning and technical development or land usage. Any additional function is useful as a supplementary for region or province planning details. This phase likewise accredits to define boundary in an open space based on geographical appearance. Informant who is categorized as an elder lives in earthquake prone area, to be precise the area is the surrounding of Mount Krakatau. The collected data is one of method for analyzed with thematic model. Later on, it will be verified. In space zoning, long-range distance sensor is applied to determine visualization of the area, which will be zoned before the step of survey to validate the data. The data, which is obtained from long-range distance sensor and site survey, will be overlaid using GIS Platform. Comparing the knowledge based on a local wisdom that is well known by elderly in that area, some of it is relevant to the research, while the others are not. Based on the site survey, the interpretation of a long-range distance sensor, and determining space zoning by considering various aspects resulted in the pattern map of space zoning. This map can be integrated with disaster mitigation affected by volcano eruption.

Keywords: elderly, GIS platform, local wisdom, space zoning

Procedia PDF Downloads 255