Search results for: medi-cal data

Authors: Hema Bhardwaj, D. Srinivasa Rao

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Technology for analysing, processing, and extracting meaningful data from enormous and complicated datasets can be termed as "big data." The technique of big data mining and big data analysis is extremely helpful for business movements such as making decisions, building organisational plans, researching the market efficiently, improving sales, etc., because typical management tools cannot handle such complicated datasets. Special computational and statistical issues, such as measurement errors, noise accumulation, spurious correlation, and storage and scalability limitations, are brought on by big data. These unique problems call for new computational and statistical paradigms. This research paper offers an overview of the literature on big data mining, its process, along with problems and difficulties, with a focus on the unique characteristics of big data. Organizations have several difficulties when undertaking data mining, which has an impact on their decision-making. Every day, terabytes of data are produced, yet only around 1% of that data is really analyzed. The idea of the mining and analysis of data and knowledge discovery techniques that have recently been created with practical application systems is presented in this study. This article's conclusion also includes a list of issues and difficulties for further research in the area. The report discusses the management's main big data and data mining challenges.

Keywords: big data, data mining, data analysis, knowledge discovery techniques, data mining challenges

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Authors: Rimmy Yadav, Anmol Preet Kaur

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Big Data has demonstrated the vast potential in streamlining, deciding, spotting business drifts in different fields, for example, producing, fund, Information Technology. This paper gives a multi-disciplinary diagram of the research issues in enormous information and its procedures, instruments, and system identified with the privacy, data storage management, network and energy utilization, adaptation to non-critical failure and information representations. Other than this, result difficulties and openings accessible in this Big Data platform have made.

Keywords: big data, privacy, data management, network and energy consumption

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Authors: Zahra Abdi, Roghayeh Alipour, Babak Farahi Ghasraboonasr

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Introduction: Diabetes is a serious medical condition that requires constant care. People with type 2 diabetes may also be likely to experience dry, itchy skin and poor wound healing. Some people with diabetes will have a skin problems at some time in their lives and for those not yet diagnosed with diabetes, a skin problem can be an indication of the disease. our purpose was to assess the capability and knowledge of students of Shiraz University of Medical Sciences about prevent from skin complications in diabetes type 2. Methods: In this descriptive cross-sectional study, knowledge of 360 students of Shiraz University of Medical Sciences was evaluated about different ways to avoid skin complications in diabetes type 2. Data were analyzed by spss19.(P<0.05) was considered significant. Results: 360 students of Shiraz University of Medical Sciences participated in this study. 45% of students agree with the effect of Moisturize skin daily, If Diabetics have sensitive skin, choose a fragrance-free, dye-free moisturizer that won’t irritate skin. 52% believe that Protect skin from sun can be so useful, Sun exposure is drying and aging. Use sunscreen with SPF 30 or higher whenever you’re outside. Wear gloves when doing yardwork to protect the skin on your hands. 62% of students strongly agree with Carefully clean any cuts and scrapes, If diabetics notice any sign of infection skin that’s red, swollen, or warm to the touch, or has a foul-smelling drainage or pus should consulting with a doctor immediately. Diabetics should be careful about any injury that takes longer than normal to heal and they should consulting with doctor about them too. 72% of students believe that diabetics should be diligent about daily foot care. Clean and moisturize feet each day and check each foot closely, top and bottom, for wounds even a tiny cut, blisters, or cracked skin. Conclusions: The risk of getting these diabetes complications can be lessened by controlling blood sugar. Skin complications can cause serious consequences. Taking care of skin is so important and using these tips are remarkable effective and help diabetics to look after their skin easier.

Keywords: skin complications, diabetes type 2, Shiraz University of Medical Sciences, diabetics

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Authors: Byung Ho Jung, Dong Hoon Lim

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Logistic regression is a statistical method for analyzing a dataset in which there are one or more independent variables that determine an outcome. Logistic regression is used extensively in numerous disciplines, including the medical and social science fields. In this paper, we address the problem of estimating parameters in the logistic regression based on MapReduce framework with RHadoop that integrates R and Hadoop environment applicable to large scale data. There exist three learning algorithms for logistic regression, namely Gradient descent method, Cost minimization method and Newton-Rhapson's method. The Newton-Rhapson's method does not require a learning rate, while gradient descent and cost minimization methods need to manually pick a learning rate. The experimental results demonstrated that our learning algorithms using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also compared the performance of our Newton-Rhapson's method with gradient descent and cost minimization methods. The results showed that our newton's method appeared to be the most robust to all data tested.

Keywords: big data, logistic regression, MapReduce, RHadoop

Procedia PDF Downloads 265

Authors: Mansoureh Ghiasabadi Farahani, Samira Kalantary, Sara Taghi-Pour, Mahboubeh Shamsi

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Nowadays, the development of computers technology and its recent applications provide access to new types of data, which have not been considered by the traditional data analysts. Two particularly interesting characteristics of such data sets include their huge size and streaming nature .Incremental learning techniques have been used extensively to address the data stream classification problem. This paper presents a concise survey on the obstacles and the requirements issues classifying data streams with using decision tree. The most important issue is to maintain a balance between accuracy and efficiency, the algorithm should provide good classification performance with a reasonable time response.

Keywords: big data, data streams, classification, decision tree

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Authors: Aishwarya Shekhar, Himanshu Sharma

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Data deduplication is one of important data compression techniques for eliminating duplicate copies of repeating data, and has been widely used in cloud storage to reduce the amount of storage space and save bandwidth. In this process, duplicate data is expunged, leaving only one copy means single instance of the data to be accumulated. Though, indexing of each and every data is still maintained. Data deduplication is an approach for minimizing the part of storage space an organization required to retain its data. In most of the company, the storage systems carry identical copies of numerous pieces of data. Deduplication terminates these additional copies by saving just one copy of the data and exchanging the other copies with pointers that assist back to the primary copy. To ignore this duplication of the data and to preserve the confidentiality in the cloud here we are applying the concept of hybrid nature of cloud. A hybrid cloud is a fusion of minimally one public and private cloud. As a proof of concept, we implement a java code which provides security as well as removes all types of duplicated data from the cloud.

Keywords: confidentiality, deduplication, data compression, hybridity of cloud

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Authors: Devatha Kalyan Kumar, Aravindraj D., Sadathulla A.

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Big data are now rapidly expanding in all engineering and science and many other domains. The potential of large or massive data is undoubtedly significant, make sense to require new ways of thinking and learning techniques to address the various big data challenges. Machine learning is continuously unleashing its power in a wide range of applications. In this paper, the latest advances and advancements in the researches on machine learning for big data processing. First, the machine learning techniques methods in recent studies, such as deep learning, representation learning, transfer learning, active learning and distributed and parallel learning. Then focus on the challenges and possible solutions of machine learning for big data.

Keywords: active learning, big data, deep learning, machine learning

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Authors: Tomy Prihananto, Damar Apri Sudarmadi

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Indonesia recognizes the right to privacy as a human right. Indonesia provides legal protection against data management activities because the protection of personal data is a part of human rights. This paper aims to describe the arrangement of data management and data management in Indonesia. This paper is a descriptive research with qualitative approach and collecting data from literature study. Results of this paper are comprehensive arrangement of data that have been set up as a technical requirement of data protection by encryption methods. Arrangements on encryption and protection of personal data are mutually reinforcing arrangements in the protection of personal data. Indonesia has two important and immediately enacted laws that provide protection for the privacy of information that is part of human rights.

Keywords: Indonesia, protection, personal data, privacy, human rights, encryption

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Authors: Melvin Ouma

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Language is one of the most crucial tools in medical interaction. Its importance is as great today as it was many decades ago. Difficulty in openly discussing certain diseases and body parts is one of the challenges in language use in medical contexts. Guided by H. P. Grice’s Cooperative Principle, this paper explores the flouting of the cooperative principles in Swahili speaking medical setting. The paper examines how men flout the maxims using the Swahili language when reporting reproductive health problems to the doctor. The data used was gathered from a qualitative study carried out in a reproductive health clinic in a public facility in Nakuru County, Kenya. All the research protocols were observed by acquiring all the research permits. Respondents' ethical considerations of consent, privacy, and confidentiality were observed. The respondents recruited were men who visited the reproductive health clinic and voluntarily agreed to participate in the study without coercion or compensation. Participant observation was the key data collection tool, with the doctor and patient conversation digitally recorded. The researcher was allowed into the clinic in a socially acceptable role. Male patients flouted the maxims of quantity, quality, relation, and manner in order to describe their reproductive health problems without embarrassment using the Swahili language. The flouting was done through the discursive strategies of narration and circumlocution. Flouting of the maxims was acceptable to the doctor and patient due to the fact that sexual intercourse and private body parts are taboo topics and uncomfortable to talk about. The quality of health care received by the patient depended on the doctor’s patience when all the maxims were flouted. In the reproductive health clinic, flouting of maxims hindered communication and, at the same time, enhanced communication between the doctor and patient.

Keywords: cooperative principle, doctor, men, reproductive health

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Authors: Dulal Bhaumik, Fei Jie, Runa Bhaumik, Bikas Sinha

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Human brain is an amazingly complex network. Aberrant activities in this network can lead to various neurological disorders such as multiple sclerosis, Parkinson’s disease, Alzheimer’s disease and autism. fMRI has emerged as an important tool to delineate the neural networks affected by such diseases, particularly autism. In this paper, we propose mixed-effects models together with an appropriate procedure for controlling false discoveries to detect disrupted connectivities in whole brain studies. Results are illustrated with a large data set known as Autism Brain Imaging Data Exchange or ABIDE which includes 361 subjects from 8 medical centers. We believe that our findings have addressed adequately the small sample inference problem, and thus are more reliable for therapeutic target for intervention. In addition, our result can be used for early detection of subjects who are at high risk of developing neurological disorders.

Keywords: ABIDE, autism spectrum disorder, fMRI, mixed-effects model

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Authors: Gamith Mendis

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Even though the doctors are knowledgeable, there's a gap between knowing and being ethical. This is a barrier to establish an ethical doctor-patient relationship. Current health system has oriented in a way that gives a meaning to both the doctor and the patient through intermediate entities. For the doctor, the meaning of the doctor-patient relationship is given through the financial benefits, promotions, and social status. For the patient, the meaning is given through curing of the disease. It is obvious that both are independent entities between the doctor and the patient. As the philosophers like Husserl and Heidegger have pointed out, our subjective world will give the immediate meaningfulness to us. We should seek this immediate meaningfulness of the doctor-patient relationship. The present research has used the existential methodology as guided self-reflections on the lived experiences of a doctor and his students. In this approach, two important aspects have been understood. The first is, establishing the fact that being ethical is itself giving meaningfulness to the doctor’s being without any mediate entities. Simply, it is enjoying being an honest being. The second is by being-with-the-patient while treating the disease; both the doctor and the patient can enjoy the meaningfulness of their human relationship. The medical students and the doctors should focus on this meaningfulness. For that, this discussion should be actively incorporated into the medical curriculum with programs of practical guidance to medical students and should be discussed in patient-care reviews in the health setting within a satisfactory framework.

Keywords: doctor-patient relationship, medical education, medical ethics, medical humanities, qualitative health research

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Authors: Amy Gooden

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When human genomic data is considered, this is often done through only one dimension of the law, or the interplay between the various dimensions is not considered, thus providing an incomplete picture of the legal framework. This research considers and analyzes the various dimensions in South African law applicable to genomic sequence data – including property rights, personality rights, and intellectual property rights. The effective use of personal genomic sequence data requires the acknowledgement and harmonization of the rights applicable to such data.

Keywords: artificial intelligence, data, law, genomics, rights

Procedia PDF Downloads 133

Authors: Umamaheswari Shanmugam, Silvia Ronchi, Radu Vornicu

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Software, artificial intelligence, and machine learning can improve healthcare through innovative and advanced technologies that are able to use the large amount and variety of data generated during healthcare services every day. As we read the news, over 500 machine learning or other artificial intelligence medical devices have now received FDA clearance or approval, the first ones even preceding the year 2000. One of the big advantages of these new technologies is the ability to get experience and knowledge from real-world use and to continuously improve their performance. Healthcare systems and institutions can have a great benefit because the use of advanced technologies improves the same time efficiency and efficacy of healthcare. Software-defined as a medical device, is stand-alone software that is intended to be used for patients for one or more of these specific medical intended uses: - diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of a disease, any other health conditions, replacing or modifying any part of a physiological or pathological process–manage the received information from in vitro specimens derived from the human samples (body) and without principal main action of its principal intended use by pharmacological, immunological or metabolic definition. Software qualified as medical devices must comply with the general safety and performance requirements applicable to medical devices. These requirements are necessary to ensure high performance and quality and also to protect patients’ safety. The evolution and the continuous improvement of software used in healthcare must take into consideration the increase in regulatory requirements, which are becoming more complex in each market. The gap between these advanced technologies and the new regulations is the biggest challenge for medical device manufacturers. Regulatory requirements can be considered a market barrier, as they can delay or obstacle the device approval, but they are necessary to ensure performance, quality, and safety, and at the same time, they can be a business opportunity if the manufacturer is able to define in advance the appropriate regulatory strategy. The abstract will provide an overview of the current regulatory framework, the evolution of the international requirements, and the standards applicable to medical device software in the potential market all over the world.

Keywords: artificial intelligence, machine learning, SaMD, regulatory, clinical evaluation, classification, international requirements, MDR, 510k, PMA, IMDRF, cyber security, health care systems.

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Authors: Onder Yakut, Serdar Solak, Emine Dogru Bolat

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Measuring the Electrocardiogram (ECG) signal is an essential process for the diagnosis of the heart diseases. The ECG signal has the information of the degree of how much the heart performs its functions. In medical diagnosis and treatment systems, Decision Support Systems processing the ECG signal are being developed for the use of clinicians while medical examination. In this study, a modular wireless ECG (WECG) measuring and recording system using a single board computer and e-Health sensor platform is developed. In this designed modular system, after the ECG signal is taken from the body surface by the electrodes first, it is filtered and converted to digital form. Then, it is recorded to the health database using Wi-Fi communication technology. The real time access of the ECG data is provided through the internet utilizing the developed web interface.

Keywords: ECG, e-health sensor shield, Raspberry Pi, wiFi technology

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Authors: X. Gumara Rigol, I. Martínez de Apellaniz Anzuola, A. Garcia Serrano, A. Franzi Cros, O. Vidal Calbet, A. Al Maruf

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Traditional federated architectures for data warehousing work well when corporations have existing regional data warehouses and there is a need to aggregate data at a global level. Schibsted Media Group has been maturing from a decentralised organisation into a more globalised one and needed to build both some of the regional data warehouses for some brands at the same time as the global one. In this paper, we present the architectural alternatives studied and why a custom federated approach was the notable recommendation to go further with the implementation. Although the data warehouses are logically federated, the implementation uses a single database system which presented many advantages like: cost reduction and improved data access to global users allowing consumers of the data to have a common data model for detailed analysis across different geographies and a flexible layer for local specific needs in the same place.

Keywords: data integration, data warehousing, federated architecture, Online Analytical Processing (OLAP)

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Authors: Maya Agarwala

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Objectives: Audit the quality of clinical photographs taken for Orthodontic patients at Queen’s hospital, Romford. Design and setting: All Orthodontic photographs are taken in the Medical Photography Department at Queen’s Hospital. Retrospective audit with data collected between January - March 2023. Gold standard: Institute of Medical Illustrators (IMI) standard 12 photographs: 6 extraoral and 6 intraoral. 100% of patients to have the standard 12 photographs meeting a satisfactory diagnostic quality. Materials and methods: 30 patients randomly selected. All photographs analysed against the IMI gold standard. Results: A total of 360 photographs were analysed. 100% of the photographs had the 12 photographic views. Of which, 93.1% met the gold standard. Of the extraoral photos: 99.4% met the gold standard, 0.6% had incorrect head positioning. Of the intraoral photographs: 87.2% met the gold standard. The most common intraoral errors were: the presence of saliva pooling (7.2%), insufficient soft tissue retraction (3.3%), incomplete occlusal surface visibility (2.2%) and mirror fogging (1.1%). Conclusion: The gold standard was not met, however the overall standard of Orthodontic photographs is high. Further training of the Medical Photography team is needed to improve the quality of photographs. Following the training, the audit will be repeated. High-quality clinical photographs are an important part of clinical record keeping.

Keywords: orthodontics, paediatric, photography, audit

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Authors: Isabell Koinig, Sandra Diehl

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In recent years, the health-care context has not been left unaffected by technological developments. In recent years, the Internet of Medical Things (IoMT)has not only led to a collaboration between disease management and advanced care coordination but also to more personalized health care and patient empowerment. With more than 40 % of all health technology being IoMT-related by 2020, questions regarding privacy become more prevalent, even more so during COVID-19when apps allowing for an intensive tracking of people’s whereabouts and their personal contacts cause privacy advocates to protest and revolt. There is a widespread tendency that even though users may express concerns and fears about their privacy, they behave in a manner that appears to contradict their statements by disclosing personal data. In literature, this phenomenon is discussed as a privacy paradox. While there are some studies investigating the privacy paradox in general, there is only scarce research related to the privacy paradox in the health sector and, to the authors’ knowledge, no empirical study investigating young people’s attitudes toward data security when using wearables and health apps. The empirical study presented in this paper tries to reduce this research gap by focusing on the area of digital and mobile health. It sets out to investigate the degree of importance individuals attribute to protecting their privacy and individual privacy protection strategies. Moreover, the question to which degree individuals between the ages of 20 and 30 years are willing to grant commercial parties access to their private data to use digital health services and apps are put to the test. To answer this research question, results from 6 focus groups with 40 participants will be presented. The focus was put on this age segment that has grown up in a digitally immersed environment. Moreover, it is particularly the young generation who is not only interested in health and fitness but also already uses health-supporting apps or gadgets. Approximately one-third of the study participants were students. Subjects were recruited in August and September 2019 by two trained researchers via email and were offered an incentive for their participation. Overall, results indicate that the young generation is well informed about the growing data collection and is quite critical of it; moreover, they possess knowledge of the potential side effects associated with this data collection. Most respondents indicated to cautiously handle their data and consider privacy as highly relevant, utilizing a number of protective strategies to ensure the confidentiality of their information. Their willingness to share information in exchange for services was only moderately pronounced, particularly in the health context, since health data was seen as valuable and sensitive. The majority of respondents indicated to rather miss out on using digital and mobile health offerings in order to maintain their privacy. While this behavior might be an unintended consequence, it is an important piece of information for app developers and medical providers, who have to find a way to find a user base for their products against the background of rising user privacy concerns.

Keywords: digital health, privacy, privacy paradox, IoMT

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Authors: Sikander Singh Cheema, Jasmeen Kaur

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In this paper, the concept of data mining is summarized and its one of the important process i.e KDD is summarized. The data mining based on Genetic Algorithm is researched in and ways to achieve the data mining Genetic Algorithm are surveyed. This paper also conducts a formal review on the area of data mining tasks and genetic algorithm in various fields.

Keywords: data mining, KDD, genetic algorithm, descriptive mining, predictive mining

Procedia PDF Downloads 583

Authors: Seung-Lock Seo

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This work presents a data-mining empirical monitoring scheme for industrial processes with partially unbalanced data. Measurement data of good operations are relatively easy to gather, but in unusual special events or faults it is generally difficult to collect process information or almost impossible to analyze some noisy data of industrial processes. At this time some noise filtering techniques can be used to enhance process monitoring performance in a real-time basis. In addition, pre-processing of raw process data is helpful to eliminate unwanted variation of industrial process data. In this work, the performance of various monitoring schemes was tested and demonstrated for discrete batch process data. It showed that the monitoring performance was improved significantly in terms of monitoring success rate of given process faults.

Keywords: data mining, process data, monitoring, safety, industrial processes

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Authors: Nami Matsumoto

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This study explores the experiences of cross-linguistic medical encounters by patients, and their views of receiving language support therein, with a particular focus on Japanese-English cases. The aim of this study is to investigate the reason for the frequent use of a spouse as a communication mediator from a Japanese perspective, through a comparison with that of English speakers. This study conducts an empirical qualitative analysis of the accounts of informants. A total of 31 informants who have experienced Japanese-English cross-linguistic medical encounters were recruited in Australia and Japan for semi-structured in-depth interviews. A breakdown of informants is 15 English speakers and 16 Japanese speakers. In order to obtain a further insight into collected data, additional interviews were held with 4 Australian doctors who are familiar with using interpreters. This study was approved by the Australian National University Human Research Ethics Committee, and written consent to participate in this study was obtained from all participants. The interviews lasted up to over one hour. They were audio-recorded and subsequently transcribed by the author. Japanese transcriptions were translated into English by the author. An analysis of interview data found that patients value relationship in communication. Particularly, Japanese informants, who have an English-speaking spouse, value trust-based communication interventions by their spouse, regardless of the language proficiency of the spouse. In Australia, health care interpreters are required to abide by the national code of ethics for interpreters. The Code defines the role of an interpreter exclusively to be language rendition and enshrines the tenets of accuracy, confidentiality and professional role boundaries. However, the analysis found that an interpreter who strictly complies with the Code sometimes fails to render the real intentions of the patient and their doctor. Findings from the study suggest that an interpreter should not be detached from the context and should be more engaged in the needs of patients. Their needs are not always communicated by an interpreter when they simply follow a professional code of ethics. The concept of relationship-centred care should be incorporated in the professional practice of health care interpreters.

Keywords: health care, Japanese-English medical encounters, language barriers, trust

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Authors: Cristina Maria Ribeiro Martins Pereira Caridade, Ana Rita Ferreira Morais

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The use of computational tools has become essential in the context of interactive learning, especially in engineering education. In the medical industry, teaching medical image processing techniques is a crucial part of training biomedical engineers, as it has integrated applications with healthcare facilities and hospitals. The aim of this article is to present a teaching-learning simulation tool developed in MATLAB using a graphical user interface for medical image fusion that explores different image fusion methodologies and processes in combination with image pre-processing techniques. The application uses different algorithms and medical fusion techniques in real time, allowing you to view original images and fusion images, compare processed and original images, adjust parameters, and save images. The tool proposed in an innovative teaching and learning environment consists of a dynamic and motivating teaching simulation for biomedical engineering students to acquire knowledge about medical image fusion techniques and necessary skills for the training of biomedical engineers. In conclusion, the developed simulation tool provides real-time visualization of the original and fusion images and the possibility to test, evaluate and progress the student’s knowledge about the fusion of medical images. It also facilitates the exploration of medical imaging applications, specifically image fusion, which is critical in the medical industry. Teachers and students can make adjustments and/or create new functions, making the simulation environment adaptable to new techniques and methodologies.

Keywords: image fusion, image processing, teaching-learning simulation tool, biomedical engineering education

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Authors: Boukhatem Mohammed Belkaid, Lahdir Mourad

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In this paper, we propose a new encryption system for security issues medical images. The hybrid encryption scheme is based on AES and RSA algorithms to validate the three security services are authentication, integrity, and confidentiality. Privacy is ensured by AES, authenticity is ensured by the RSA algorithm. Integrity is assured by the basic function of the correlation between adjacent pixels. Our system generates a unique password every new session of encryption, that will be used to encrypt each frame of the medical image basis to strengthen and ensure his safety. Several metrics have been used for various tests of our analysis. For the integrity test, we noticed the efficiencies of our system and how the imprint cryptographic changes at reception if a change affects the image in the transmission channel.

Keywords: AES, RSA, integrity, confidentiality, authentication, medical images, encryption, decryption, key, correlation

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Authors: Farida Habib, Haya Alfozan, Eman Miligi, Najla Alotaibi

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Background: Women’s satisfaction with maternity services, especially care during labor and birth, has become highly significant to healthcare providers, administrators, and policymakers. Purpose: The aims of this study were to assess maternal satisfaction regarding the quality of care during labor and to compare the level of maternal satisfaction between women who delivered by physicians and those delivered by midwives. Methodology: A descriptive, cross-sectional, correlational design was used. A convenient sample of 180 low-risk cases of immediate postpartum women who delivered at King Abdul-Aziz medical city was recruited. Women whose babies were diagnosed with serious health problems were excluded from the study. Data were collected using a self-administered questionnaire. The validity and reliability of the questionnaire were ensured. The questionnaire included three parts, namely: demographics data, medical history, and obstetrical history, and the last part is the satisfaction assessment tool. Ethical confederations were ensured. Maternal satisfaction during labor was classified in terms of health care, health workers' communication, and the environment. Results: Regarding health care, women were highly satisfied with care received from nurse (M = 4.21 + 0.88), medical care received (M = 4.17 + 0.79), and comfort techniques (M = 4.04 + 0.91). Regarding health workers' communication, women were highly satisfied with the provider to treat with dignity and respect (M = 4.03 + 0.91) and orientation to the toilet, bathroom, washing area (M = 4.00 + 0.93). Regarding the environment, women were highly satisfied with the experience of their baby's birth (M = 4.18 + 0.98) and supplies with drugs and supplies (M = 4.09 + 0.97). There was no statistically significant difference in maternal satisfaction between women who delivered by physicians and those delivered by midwives. Conclusion: Women were generally satisfied with their labor and delivery experience. There was no difference in maternal satisfaction on the labor process between women who delivered by physicians and those delivered by midwives.

Keywords: maternity, satisfaction, labor, delivery

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Authors: Chaimaa Messaoudi, Rachida Fissoune, Hassan Badir

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Technological advances of computer science and data analysis are helping to provide continuously huge volumes of biological data, which are available on the web. Such advances involve and require powerful techniques for data integration to extract pertinent knowledge and information for a specific question. Biomedical exploration of these big data often requires the use of complex queries across multiple autonomous, heterogeneous and distributed data sources. Semantic integration is an active area of research in several disciplines, such as databases, information-integration, and ontology. We provide a survey of some approaches and techniques for integrating biological data, we focus on those developed in the ontology community.

Keywords: biological ontology, linked data, semantic data integration, semantic web

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Authors: Bhavani Veasuvalingam

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Case-based learning (CBL) is a popular instructional method aimed to bridge theory to clinical practice. This study aims to explore CBL mixed modality curriculum in influencing students’ learning styles and strategies that support learning. An explanatory sequential mixed method study was employed with initial phase, 44-itemed Felderman’s Index of Learning Style (ILS) questionnaire employed across year one medical students (n=142) using convenience sampling to describe the preferred learning styles. The qualitative phase utilised three focus group discussions (FGD) to explore in depth on the multimodal learning style exhibited by the students. Most students preferred combination of learning stylesthat is reflective, sensing, visual and sequential i.e.: RSVISeq style (24.64%) from the ILS analysis. The frequency of learning preference from processing to understanding were well balanced, with sequential-global domain (66.2%); sensing-intuitive (59.86%), active- reflective (57%), and visual-verbal (51.41%). The qualitative data reported three major themes, namely Theme 1: CBL mixed modalities navigates learners’ learning style; Theme 2: Multimodal learners active learning strategies supports learning. Theme 3: CBL modalities facilitating theory into clinical knowledge. Both quantitative and qualitative study strongly reports the multimodal learning style of the year one medical students. Medical students utilise multimodal learning styles to attain the clinical knowledge when learning with CBL mixed modalities. Educators’ awareness of the multimodal learning style is crucial in delivering the CBL mixed modalities effectively, considering strategic pedagogical support students to engage and learn CBL in bridging the theoretical knowledge into clinical practice.

Keywords: case-based learning, learnign style, medical students, learning

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Authors: Shalinawati Ramli, Khairani Omar, Nurul Azmawati Mohamed, Zarini Ismail, Nur Syahrina Rahim, Nurul Hayati Chamhuri

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Medical doctors’ work to prevent, diagnose, treat diseases, disorders, and injuries as well as prescribing medication. Many people are attracted to this profession because it gives them the opportunity to help others. Doctors’ improve quality of life by providing advice, healing physical ailments and performing complex surgeries. Medicine is a profession in which dedication to the wellbeing of others is of paramount importance. Balancing the requirements of work and personal life can be a struggle as the demand of work as a doctors’ is great. Perception and expectation of medical students regarding the lifestyle of doctors’ is important to ensure that they had made the right career choice. Thus, the aim of this study is to assess the perception of pre-clinical students regarding doctors’ lifestyle. This study is a cross-sectional study involving all third-year pre-clinical medical students at University Sains Islam Malaysia. A total of 81 students participated in this study. Participants were given a set of questionnaire consisting of demographic data, open-ended questions on their perception on doctors’ lifestyle of working environment, salary expectation and family life. Thematic analysis were used to analyse the data. The participants comprised 69% female and their age range was between 20-21 years old. Majority of them were from middle-income families. Majority of the students perceived that the doctors’ lifestyle would be busy (72%). Approximately 30% of them expected that the time schedule will be unpredictable, 21% mentioned that sacrifice is required and 16% perceived it as a tiring job. Other themes emerged were ‘requiring high commitment’ (6%), challenging (7%) and risky (4%). With regards to salary expectation, 48% expected reasonable salary, 33% high salary and 12% described it as 'not worth compared to the workload'. Majority of them perceived that their family life will be restricted (62%) and time management is important (33%). Only 15% mentioned that family members have to sacrifice and spousal understanding is important (7%). About 10% of them perceived that their family will not be affected by their profession. Majority of the medical students perceived a busy doctors’ lifestyle, reasonable salary and restricted family life. However, there was a significant proportion of them who required counselling for better preparation of their future lifestyle.

Keywords: doctors lifestyle, pre-clinical students, perception, understanding

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Authors: Thrivikraman Aswathi, S. Advaith

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As there can be cases where the use of real data is somehow limited, such as when it is hard to get access to a large volume of real data, we need to go for synthetic data generation. This produces high-quality synthetic data while maintaining the statistical properties of a specific dataset. In the present work, a generative adversarial network (GAN) is trained to produce multivariate time series (MTS) data since the MTS is now being gathered more often in various real-world systems. Furthermore, the GAN-generated MTS data is fed into a transformer-based deep learning architecture that carries out the data categorization into predefined classes. Further, the model is evaluated across various distinct domains by generating corresponding MTS data.

Keywords: GAN, transformer, classification, multivariate time series

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Authors: H. Jalahi, A. Yazdanpanah Nozari

Abstract:

Background and Purpose: Assessment of learners’ performance is an important factors in teaching-learning process. When a factor is sensitive and has high influence on life, their assessment should be done precisely. Thinking dispositions are very important factors in medical education because of its specific condition. In this study a model is designed for fostering thinking dispositions of learners in which authentic assessment is an important element. Materials and Methods: Objective based research is developmental, and such a model was not designed for curricula. Data collection and comparing approaches about assessment and analyzing current assessments offered applied proposals. Results: Based on research findings, the current assessments are response-based, that is students instead of product of response, only offers the specific response which the teachers expects; but authentic assessment is a form of assessment in which students are asked to perform real-word tasks that demonstrate meaningful application of essential knowledge and skills. Conclusion: Because of the difficulties and unexpected problems in life and individuals needs to lifelong learning and conditions in medical course that require decision making in specific times, we must pay attention to reach thinking dispositions and it should be included in curriculum. Authentic assessment as an important aspect of curriculum can help fostering thinking dispositions of learners. Using this kind of assessments which focus on application of information and skills to solve real-word tasks have more important role in medical courses.

Keywords: assessment, authentic, medical courses, developmental

Procedia PDF Downloads 357

Authors: Lakshmi Prayaga, Chandra Prayaga. Aaron Wade, Gopi Shankar Mallu, Harsha Satya Pola

Abstract:

Synthetic data generated by Generative Adversarial Networks and Autoencoders is becoming more common to combat the problem of insufficient data for research purposes. However, generating synthetic data is a tedious task requiring extensive mathematical and programming background. Open-source platforms such as the Synthetic Data Vault (SDV) and Mostly AI have offered a platform that is user-friendly and accessible to non-technical professionals to generate synthetic data to augment existing data for further analysis. The SDV also provides for additions to the generic GAN, such as the Gaussian copula. We present the results from two synthetic data sets (CTGAN data and CTGAN with Gaussian Copula) generated by the SDV and report the findings. The results indicate that the ROC and AUC curves for the data generated by adding the layer of Gaussian copula are much higher than the data generated by the CTGAN.

Keywords: synthetic data generation, generative adversarial networks, conditional tabular GAN, Gaussian copula

Procedia PDF Downloads 62

Authors: Naima Fatehi

Abstract:

The paper reports on 107 medicinal plants, traditionally used in the South-West of Algeria (Bechar region). The information has been documented by interviewing traditional herbalists, various elderly men and women following different ethnobotanical methods. Ethnobotanical data was arranged alphabetically by botanical name, followed by family name, vernacular name, and part used. The present paper represents significant ethnobotanical information on medical plants used extensively in Bechar region for treating various diseases and provides baseline data for future pharmacological and phytochemical studies.

Keywords: medicinal plants, ethnobotanical survey, South-West Algeria, Bechar region

Procedia PDF Downloads 512