Search results for: medical assessments

Authors: Suppawan Lertpongpakpoom, Anongnat Boonrat, Kunya BoontummoSuppawan

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This descriptive cost analysis aimed to analyze the unit cost of patients in medical intensive care unit. Purposive sampling was used to select 20 nurses, 6 practical nurses, 5 nurses aid and select samples 30 patients. Data were collected from both primary source (activity and average time of nursing care) and secondary source Z bill of payment and patient record). Instruments were cost recording form, activity observation form, and service recording form. Content validity of all instruments were evaluated by three experts (CVI = 0.87). Descriptive statistics was employed for data analysis. The results of the Activity-Based Costing Analysis showed that total activity cost of 4 service types for the patients was 14,776.92 Bath. The highest cost was nursing record was 5,674.78 Bath, followed direct nursing activity was 5,176.18 Bath, medical treatment was 1,976.6 Bath. The lowest cost was management activity was 1,003.64 Bath per visit. The result suggested that Activity-Base Costing Analysis could be applied to give better understanding of cost structure, enabling better consideration wasted expense and non-value-added activity, and improvement of effective utilization.

Keywords: activity-based costing, medical intensive care, nursing care, cost analysis

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Authors: Yan Yue

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Epistemic stance refers to the writer’s judgement about the certainty of the proposition, which demonstrates writer’s degree of commitment and confidence to the status of the information. Epistemic stance can exert great consequence to the validity or reliability of the values of a statement, however, to date, it receives little attention in translations studies, especially from the perspective of systemic functional linguistics (SFL) and with the relation to translator’s domain knowledge. This study is corpus-based research carried out in SFL perspective, which investigates translator’s epistemic stance pattern in Chinese medicine discourse translations by translators with and without medical domain knowledge. Overall, our findings show that all translators tend to be neither too assertive nor too doubted about Chinese medicine statements, and they all tend to express their epistemic stance in a subjective rather than objective way. Individually, there is a clear pattern of epistemic stance marked off by translators’ medical expertise, which further consolidates the previous finding that epistemic asymmetry is found most salient between lay people and professionals. However, contrary to our hypothesis, translators as clinicians who have more medical knowledge are found to be more tentative to TCM statements than translators as non-clinicians. This finding could serve to refine the statements about the relation between writer’s domain knowledge and epistemic stance-taking and the current debate whether Chinese medicine texts should only be translated by clinicians.

Keywords: epistemic stance, domain knowledge, SFL, medical translation

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Authors: Said Ettaieb, Kamel Hamrouni, Su Ruan

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This paper presents a new method based both on Active Shape Model and a priori knowledge about the spatio-temporal shape variation for tracking deformable structures in medical imaging. The main idea is to exploit the a priori knowledge of shape that exists in ASM and introduce new knowledge about the shape variation over time. The aim is to define a new more stable method, allowing the reliable detection of structures whose shape changes considerably in time. This method can also be used for the three-dimensional segmentation by replacing the temporal component by the third spatial axis (z). The proposed method is applied for the functional and morphological study of the heart pump. The functional aspect was studied through temporal sequences of scintigraphic images and morphology was studied through MRI volumes. The obtained results are encouraging and show the performance of the proposed method.

Keywords: active shape model, a priori knowledge, spatiotemporal shape variation, deformable structures, medical images

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Authors: Md. Lutfor Rahman, Shaikh Md. Mominul Alam

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Sometimes it causes external bleeding when human skin gets seriously injured. Natural source-based blood-clotting bandages are rarely used. The available chemically treated blood clotting materials sometimes show adverse effects and are not effective in quick recovery. Considering these facts, a new blood clotting woven wound dressing product has been developed which is a combination of Micania micrantha extract with woven fabric by absorption process. This product can be represented as an important addition to medical textiles. To develop a dressing material, Micania micrantha leaf juice was applied on bleached woven fabric, followed by sun drying. The effectiveness of this woven sample was tested on volunteers. It was observed that Micania micrantha containing woven sample has a tremendous effect over conventional wound dressing materials. This result is a milestone for the textile and medical sector.

Keywords: blood clotting, Micania micrantha, medical textiles, woven fabric

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Authors: S. Saju, G. Thirugnanam

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In this paper, a medical image watermarking algorithm based on contourlet is proposed. Medical image watermarking is a special subcategory of image watermarking in the sense that images have special requirements. Watermarked medical images should not differ perceptually from their original counterparts because clinical reading of images must not be affected. Watermarking techniques based on wavelet transform are reported in many literatures but robustness and security using contourlet are better when compared to wavelet transform. The main challenge in exploring geometry in images comes from the discrete nature of the data. In this paper, original image is decomposed to two level using contourlet and the watermark is embedded in the resultant sub-bands. Sub-band selection is based on the value of Peak Signal to Noise Ratio (PSNR) that is calculated between watermarked and original image. To extract the watermark, Kernel ICA is used and it has a novel characteristic is that it does not require the transformation process to extract the watermark. Simulation results show that proposed scheme is robust against attacks such as Salt and Pepper noise, Median filtering and rotation. The performance measures like PSNR and Similarity measure are evaluated and compared with Discrete Wavelet Transform (DWT) to prove the robustness of the scheme. Simulations are carried out using Matlab Software.

Keywords: digital watermarking, independent component analysis, wavelet transform, contourlet

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Authors: Connie Edang, Siti Arpah Noordin, Shamila Mohamed Shuhidan

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For the past few decades, there are growing numbers of knowledge based industries in Malaysia. As competitive edge has become so important nowadays, the consideration of research and development (R&D) should be put at the highest priority. Alike other industries, HEIs are also contributors to the nation’s development and wealth. Hence, to become a hub for creating a knowledge-based society, HEIs not only responsible for producing skillful human capital, but also to get involved in R&D. With the importance of R&D in today’s modern economy and the rise of Science and Technology, it gives opportunities for researchers to explore this sector as to place Malaysia as a provider in some key strategic industries, including medical and health sciences field. Academic researchers/medical researchers possess unique tacit and skills based in accordance with their experience and professional expert areas. In completing a collaborative research work, there must be platforms to enable the conversion of their knowledge hence beneficial towards creation of new knowledge. The objectives of this study are to: i) explore the knowledge creation activities of medical researchers in the Malaysian Higher Education Institution (HEI); ii) explore the driving forces for knowledge creation activities among the researchers; and iii) explore the interpretation of medical researchers on the establishment of ‘ba’ in the creation of knowledge. Based on the SECI model was introduced by Nonaka and Takeuchi and the Japanese concept of ‘ba’, a qualitative study whereby semi structured interview was used as to gather the informants’ viewpoints and insights based on their experience capitalizing ‘ba’ to support their knowledge creation activities. A single the study was conducted at one of the HEIs located in Sabah. From this study, both face to face and the ICT-assisted tools are found to be significant to support interaction of their knowledge. ICT seems to ease their interaction with other research collaborator. However, this study revealed that interaction conducted in physical settings is still be best preferred by the medical researchers especially situations of whereby their knowledge is hard to be externalized. Moreover, it revealed that motivational factors play important roles as for driving forces affecting their knowledge creation activities. Other than that, the medical researchers addressed that the mix interaction bring forth value in terms of facilitating knowledge creation. Therefore this study would benefit the institution to highly optimize the utilization of good platform so that knowledge can be transferred and be made used by others in appropriate ways.

Keywords: ‘ba’, knowledge creation dynamics, Malaysia, higher education institution, medical researchers

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Authors: Fauzi Jarushi, Sinan Mohsin AlKaabi

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The Standard Penetration Test (SPT) is the most common insitu test for soil investigations. On the other hand, the Cone Penetration Test (CPT) is considered one of the best investigation tools. Due to the fast and accurate results that can be obtained it complaints the SPT in many applications like field explorations, design parameters, and quality control assessments. Many soil index and engineering properties have been correlated to both of SPT and CPT. Various foundation design methods were developed based on the outcome of these tests. Therefore it is vital to correlate these tests to each other so that either one of the tests can be used in the absence of the other, especially for preliminary evaluation and design purposes. The primary purpose of this study was to investigate the relationships between the SPT and CPT for different types of soil in Florida. Data for this research were collected from number of projects sponsored by the Florida Department of Transportation (FDOT), six sites served as the subject of SPT-CPT correlations. The correlations were established between the cone resistance (qc) and the SPT blows (i.e., N) for various soils. A positive linear relationship was found between fs and N for various soils. In general, qc versus N showed higher correlation coefficients than fs versus N. qc/N ratios were developed for different soil types and compared to literature values, the results of this research revealed higher ratios than literature values.

Keywords: in situ tests, correlation, SPT, CPT

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Authors: M. Aljumaan, F. Alkhadra, A. Aldajani, M. Alarfaj, A. Alawami, Y. Aljamaan

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Introduction: The internet has been widely available with 18 million users in Saudi Arabia alone. It was shown that 58% of Saudis are using the internet as a source of health-related information which may contribute to overcrowding of the Emergency Room (ER). Not many studies have been conducted to show the effect of online searching for health related information (HRI) and its role in influencing internet users to visit various health care facilities. So the main objective is to determine a correlation between HRI website use and health care facility visits in Saudi Arabia. Methodology: By conducting a cross sectional study and distributing a questionnaire, a total number of 1095 people were included in the study. Demographic data was collected as well as questions including the use of HRI websites, type of websites used, the reason behind the internet search, which health care facility it lead them to visit and whether seeking health information on the internet influenced their attitude towards visiting health care facilities. The survey was distributed using an internet survey applications. The data was then put on an excel sheet and analyzed with the help of a biostatician for making a correlation. Results: We found 91.4% of our population have used the internet for medical information using mainly General medical websites (77.8%), Forums (34.2%), Social Media (21.6%), and government websites (21.6%). We also found that 66.9% have used the internet for medical information to diagnose and treat their medical conditions on their own while 34.7% did so due to the inability to have a close referral and 29.5% due to their lack of time. Searching for health related information online caused 62.5% of people to visit health care facilities. Outpatient clinics were most visited at 77.9% followed by the ER (27.9%). The remaining 37.5% do not visit because using HRI websites reassure them of their condition. Conclusion: In conclusion, there may be a correlation between health information website use and health care facility visits. However, to avoid potentially inaccurate medical information, we believe doctors have an important role in educating their patients and the public on where to obtain the correct information & advertise the sites that are regulated by health care officials.

Keywords: ER visits, health related information, internet, medical websites

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Authors: Anduela Lile

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The purpose of this cross sectional study was to investigate the effectiveness of teaching and learning Statistics from a student centered perspective in higher education institutions. Statistics education has emphasized the application of tangible and interesting examples in order to motivate students learning about statistical concepts. Participants in this study were 112 bachelor students enrolled in the ‘Applied Statistics’ course in Sports University of Tirana. Experimental group students received a student-centered teaching approach; Control group students received an instructor-centered teaching approach. This study found student-centered approach student group had statistically significantly higher assessments scores (52.1 ± 18.9) at the end of the evaluation compared to instructor-centered approach student group (61.8 ± 16.4), (t (108) = 2.848, p = 0.005). Results concluded that student-centered perspective can improve student positive attitude to statistical methods and to motivate project work. Therefore, findings of this study may be very useful to the higher education institutions to establish their learning strategies especially for courses related to Statistics.

Keywords: student-centered, instructor-centered, course assessment, learning outcomes, applied statistics

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Authors: Rusne Kregzdaite, Erika Godlevska, Morta Vidunaite

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The main aim of this research is to explore existing methodologies for artists’ labour force and create artists’ socio-economic and creative conditions in an assessment model. Artists have dual aims in their creative working process: 1) income and 2) artistic self-expression. The valuation of their conditions takes into consideration both sides: the factors related to income and the satisfaction of the creative process and its result. The problem addressed in the study: tangible and intangible artists' criteria used for assessments creativity conditions. The proposed model includes objective factors (working time, income, etc.) and subjective factors (salary covering essential needs, self-satisfaction). Other intangible indicators are taken into account: the impact on the common culture, social values, and the possibility to receive awards, to represent the country in the international market. The empirical model consists of 59 separate indicators, grouped into eight categories. The deviation of each indicator from the general evaluation allows for identifying the strongest and the weakest components of artists’ conditions.

Keywords: artist conditions, artistic labour force, cultural policy, indicator, assessment model

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Authors: Loong Qing Zhe, Foo Jing Heng

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A variety of data files are now available on the internet due to the advancement of technology across the globe today. As more and more data are being uploaded on the internet, people are becoming more concerned that their private data, particularly medical health records, are being compromised and sold to others for money. Hence, the accessibility and confidentiality of patients' medical records have to be protected through electronic means. Blockchain technology is introduced to offer patients security against adversaries or unauthorised parties. In the blockchain network, only authorised personnel or organisations that have been validated as nodes may share information and data. For any change within the network, including adding a new block or modifying existing information about the block, a majority of two-thirds of the vote is required to confirm its legitimacy. Additionally, a consortium permission blockchain will connect all the entities within the same community. Consequently, all medical data in the network can be safely shared with all authorised entities. Also, synchronization can be performed within the cloud since the data is real-time. This paper discusses an efficient method for storing and sharing electronic health records (EHRs). It also examines the framework of roles within the blockchain and proposes a new approach to maintain EHRs with keyword indexes to search for patients' medical records while ensuring data privacy.

Keywords: healthcare sectors, distributed system, blockchain, electronic health records (EHR)

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Authors: B. Karabuluter, O. Karaduman

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Connected-Vehicles consists of intelligent vehicles, each of which can communicate with each other. Smart Cities are the most prominent application area of intelligent vehicles that can communicate with each other. The most important goal that is desired to be realized in Smart Cities planned for facilitating people's lives is to make transportation more comfortable and safe with intelligent/autonomous/driverless vehicles communicating with each other. In order to ensure these, the city must have communication infrastructure in the first place, and the vehicles must have the features to communicate with this infrastructure and with each other. In this context, intelligent transport studies to solve all transportation and traffic problems in classical cities continue to increase rapidly. In this study, current connected-vehicle applications developed for smart cities are considered in terms of communication techniques, vehicular networking, IoT, urban transportation implementations, intelligent traffic management, road safety, self driving. Taxonomies and assessments performed in the work show the trend of studies in inter-vehicle communication systems in smart cities and they are contributing to by ensuring that the requirements in this area are revealed.

Keywords: smart city, connected vehicles, infrastructures, VANET, wireless communication, intelligent traffic management

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Authors: Nurul Izzah Ibrahim, Isa Naina Mohamed, Norazlina Mohamed, Ahmad Nazrun Shuid

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Osteoporosis disease delays fracture healing. Statins have shown potential for osteoporosis and to promote fracture healing. The effects of statin can be further potentiated by combining it with a carrier known as poly-(DL-lactide), which would provide persistent release of statin to the fracture site. This study was designed to investigate the effects of direct injection of poly-(DL-lactide)-incorporated lovastatin on fracture healing of postmenopausal osteoporosis rat model. Twenty-four Sprague-Dawley female rats were divided into 3 groups: sham-operated (SO), ovariectomized-control rats (OVxC) and poly-(DL-lactide)-incorporated lovastatin (OVx+Lov) groups. The OVx+Lov group was given a single injection of 750 µg/kg lovastatin particles incorporated with poly-(DL-lactide). After 4 weeks, the fractured tibiae were dissected out for biomechanical assessments of the callus. The OVx+Lov group showed significantly better callus strength than the OVxC group (p<0.05). In conclusion, a single injection of lovastatin-incorporated poly-(DL-lactide) was able to promote better fracture healing of osteoporotic bone.

Keywords: statins, fracture healing, osteoporosis, poly-(DL-lactide)

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Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

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The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluate the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: convolutional neural network, electronic medical record, feature representation, lexical semantics, semantic decision

Procedia PDF Downloads 124

Authors: Umamaheswari Shanmugam, Silvia Ronchi

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Software, artificial intelligence, and machine learning can improve healthcare through innovative and advanced technologies that can use the large amount and variety of data generated during healthcare services every day; one of the significant advantages of these new technologies is the ability to get experience and knowledge from real-world use and to improve their performance continuously. Healthcare systems and institutions can significantly benefit because the use of advanced technologies improves the 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 protect patients' safety. The evolution and the continuous improvement of software used in healthcare must consider 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's approval. Still, they are necessary to ensure performance, quality, and safety. At the same time, they can be a business opportunity if the manufacturer can define the appropriate regulatory strategy in advance. 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: Sabah Mohammed, Jinan Fiaidhi, Darien Sawyer

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Data integration of health through connected services can save lives in the event of a medical emergency or provide efficient and effective interventions for the benefit of the patients through the integration of bedside and bench side clinical research. Such integration will support all wind of change in healthcare by being predictive, pre-emptive, personalized, problem-oriented and participatory. Prototyping a healthcare system that enables data integration has been a big challenge for healthcare for a long time. However, an innovative solution started to emerge by focusing on problem lists where everything can connect the problem list forming a growing graph. This notion was introduced by Dr. Lawrence Weed in early 70’s, but the enabling technologies weren’t mature enough to provide a successful implementation prototype. In this article, we are describing our efforts in prototyping Dr. Lawrence Weed's problem-oriented medical record (POMR) and his patient case schema (SOAP) to shape a prototype for connected health. For this, we are using the TypeGraphQL API and our enterprise-based QL4POMR to describe a Web-Based gateway for healthcare services connectivity. Our prototype has reported success in connecting to the HL7 FHIR medical record and the OpenTarget biomedical repositories.

Keywords: connected health, problem-oriented healthcare record, SOAP, QL4POMR, typegraphQL

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Authors: Shu Tao, Rong Wang, Huizhong Shen, Ye Huang

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High-resolution mapping of fuel combustion is essential for reducing uncertainties in assessments of greenhouse gases and air pollutant emissions. Such inventories provide valuable information for inferring carbon sinks, modeling pollutant transport, and developing control strategies. Previous inventories included only a few fuel types and were derived using national population proxies which may distort the geographical variation within countries. In this study, a global 0.1 degree by 0.1 degree geo-referenced inventory of fuel combustion (PKU-FUEL-2007) was developed for 64 fuel sub-types along with uncertainty analysis for the year 2007. Sub-national fuel consumption of large countries and major power-station locations were used. The disaggregation error can be reduced significantly by using the sub-nationally energy data, because the uneven distribution of per-capita fuel consumption within countries is taken into consideration. The PKU-FUEL was used to generate global emission inventories of CO2 (PKU-CO2-2007), polycyclic aromatic hydrocarbons (PKU-PAHs-2007), and black carbons (PKU-BC-2007). Atmospheric transport modeling and expsoure assessment were conducted for BC and PAHs based on the inventory.

Keywords: fuel, emission, BC, PAHs, atmospheric transport, exposure

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Authors: Syue-Wen Lin

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Objective: This article discusses the nursing experience of caring for a uterine cancer patient who experienced cardiogenic shock and was weaned off ECMO. The patient was placed on ECMO due to cardiogenic shock and initially struggled with anxiety caused by the physical discomfort from the disease and multiple medical devices, as well as the isolation in the ICU and restrictions on physical activity. Over time, the patient was able to wean off ECMO and perform daily activities and rehabilitation independently. Methods: The nursing period was from January 6 to January 9. Through observation, direct care, interviews, physical assessments, and case reviews, the intensive care team and bypass personnel conducted a comprehensive assessment using Gordon's 11 functional health patterns. The assessment identified three main nursing health problems: pain, anxiety, and decreased cardiac tissue perfusion. Results: The author consulted a psychologist to employ open communication techniques and empathetic care to build a trusting nurse-patient relationship. A patient-centered intensive cancer care plan was developed. Pain was assessed using a pain scale, and pain medications were adjusted in consultation with a pharmacist. Lavender essential oil therapy, light music, and pillows were used to distract and alleviate pain. The patient was encouraged to express feelings and family members were invited to increase visits and provide companionship to reduce the uncertainty caused by cancer and illness. Vital signs were closely monitored, and nursing interventions were provided to maintain adequate myocardial perfusion. Post-ECMO, the patient was encouraged to engage in rehabilitation and cardiopulmonary training. Conclusion: A key takeaway from the care process is the importance of observing not only the patient's vital signs but also their psychological state, especially when dealing with cancer patients on ECMO. The patient's greatest source of comfort was the presence of family, which helped alleviate anxiety. Healthcare providers play multiple critical roles as advocates, coordinators, educators, and counselors, listening to and accepting the patient’s emotional responses. The report aims to provide clinical cancer nurses with a reference to improve the quality of care and alleviate cancer-related discomfort.

Keywords: ECMO, uterine cancer, palliative care, Gordon's 11 functional health patterns

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Authors: Yakubu Bala Mohammed, Nadire Chavus, Mohammed Bulama

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Generative Pre-trained Transformer (ChatGPT) represents an artificial intelligence (AI) tool capable of swiftly generating comprehensive responses to prompts and follow-up inquiries. This emerging AI tool was introduced in November 2022 by OpenAI firm, an American AI research laboratory, utilizing substantial language models. This present study aims to delve into the potential future consequences of ChatGPT usage in education using AI-based algorithms. The paper will bring forth the likely potential risks of ChatGBT utilization, such as academic integrity concerns, unfair learning assessments, excessive reliance on AI, and dissemination of inaccurate information using four machine learning algorithms: eXtreme-Gradient Boosting (XGBoost), Support vector machine (SVM), Emotional artificial neural network (EANN), and Random forest (RF) would be used to analyze the study collected data due to their robustness. Finally, the findings of the study will assist education stakeholders in understanding the future implications of ChatGPT usage in education and propose solutions and directions for upcoming studies.

Keywords: machine learning, ChatGPT, education, learning, implications

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Authors: Amel Fayed, Shaden AlSubaih, Nouf Al-Qahtani, Asmaa Gosty, Asma Aljuhaimi

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Introduction: Sleep difficulties are vastly predominant among adults and affect different aspects of their life. Many literatures found out that females are more liable to suffer from sleeping problems. College students are typical example of people dealing with daily pressure and stress to fulfill the daily tasks and responsibilities. In addition to their ultimate goal of achieving excellent academic records which require their full concentration and effort. Consequently, many of them start complaining of sleep deprivations which can undesirably affect their academic achievements. This study was aiming to investigate how prevalent is sleeping disorders among different colleges in the university and its relation their academic achievements. Methods: A cross-sectional study of female university students at Princess Norah Bint Abdulrahman University using self-administered questionnaire was conducted. Insomnia Severity Index (ISI) was used to assess different grades of insomnia. Students were requested to answer the questions evaluating their sleeping habits over the last two weeks. Participants reported their latest Grade Point Average (GPA). According to ISI, insomnia severity is reported as ‘No clinically significant’, ‘Subthreshold ‘,’ Clinical moderate insomnia’ and ‘Clinical severe’. Results: In the current study, 228 students participated; 172(75.4%) from medical colleges and 56 (24.6%) from non-medical colleges. About 80% of them claimed to have never taken any medications to help them sleep while only three students confirmed their regular use of sleep-inducing medications. About 16% of the students drink milk or other hot drinks to help them fall asleep. None of the students was suspected of having obstructive sleep apnea or apparent psychiatric disorder. According to ISI, 182 (79.8%) students suffered from subthreshold insomnia, 37 (16.2%) had clinical insomnia (moderate severity) and 9 (3.9%) of students had sleeping problems of non-clinically significance level. However, none of students was found to have severe clinical insomnia. Clinical moderate insomnia was reported in 15.1% of medical students and 19.6% of non-medical students. Moreover, about 82% of medical students suffered from subthreshold insomnia compared to 73.2% of non-medical students. This difference was not statistically significant (P=0.24). About 63% of medical students and 48% of non-medical students believed that high percentage of their colleagues are suffering from insomnias (p-value 0.08) The association between GPA and insomnia revealed that; 19.5% of low GPA group compared to 9.3% of high GPA group had clinical moderate insomnia. This association was not statistically significant (p=0.15). The correlation between the GPA and the ISI score was negative but not conclusive (r=-0.08, p-value = 0.29). More than 92% of all students agreed that sleeping problems affect their academic achievement to varying degrees. Conclusion: our results suggest that insomnia is commonly prevalent among female university students and might affect the students’ achievement. This study provides preliminary data about the quality of sleep among medical and non-medical university students which may be used to promote the healthy sleeping habits among female students.

Keywords: academic achievement, females, insomnia, university student

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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: Hamidreza Sharifan, Audra Morse

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Accurate assessments of contaminant concentrations based on traditional grab sampling methods are not always possible. Passive samplers offer an attractive alternative to traditional sampling methods that overcomes these limitations. The POCIS approach has been used as a screening tool for determining the presence/absence, possible sources and relative amounts of organic compounds at field sites. The objective for the present research is on mass transfer of five water contaminants (atrazine, caffeine, bentazon, ibuprofen, atenolol) through the Water Boundary Layer (WBL) and membrane. More specific objectives followed by establishing a relationship between the sampling rate and water solubility of the compounds, as well as comparing the molecular weight of the compounds and concentration of the compounds at the time of equilibrium. To determine whether water boundary layer effects transport rate through the membrane is another main objective in this paper. After GC mass analysis of compounds, regarding the WBL effect in this experiment, Sherwood number for the experimental tank developed. A close relationship between feed concentration of compound and sampling rate has been observed.

Keywords: passive sampler, water contaminants, PES-transfer rate, contaminant concentrations

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Authors: Mahmoud Ghazy, Ahmed R. Z. Baghdadi

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Background: With the perceived pain and poor function experienced following total hip Arthroplasty (THA), patients usually feel un-satisfied. Methods: Thirty patients with THA (group I) and thirty indicated for arthroplasty but weren’t operated on yet (group II) participated in the study. The mean age was 54.53±3.44 and 55.33±2.32 years and BMI 35.7±3.03 and 35.73±1.03 kg/m2 for group I and III respectively. The Berg Balance Scale (BBS), Timed Up-and-Go (TUG) and Stair-Climbing (SC) tests were used for assessment. Assessments were conducted four weeks pre- and post-operatively and three months post-operatively with the control group being assessed at the same time intervals. The post-operative rehabilitation involved hospitalization (1st week), home-based (2nd-4th weeks), and outpatient clinic (5th-12th weeks) programs. Results: group I had significantly lower TUG and SC time compared with group II four weeks and three months post-operatively. Moreover, the BBS scores increased significantly and the pain scores and TUG and SC time decreased significantly four weeks and three months post-operatively compared with four weeks pre- operatively in group. But no significant differences in BBS scores four weeks and three months post-operatively in group I compared with group II. Interpretation/Conclusion : Patients with THA still have defects in proprioception, so they needs more concentration on proprioception training.

Keywords: dynamic balance, functional performance, hip arthroplasty, total

Procedia PDF Downloads 372

Authors: S. Vavias, T. R. Brewer, T. S. Farewell

Abstract:

Coastal floods have been identified as an important natural hazard that can cause significant damage to the populated built-up areas, related infrastructure and also ecosystems and habitats. This study attempts to fill the gap associated with the development of preliminary assessments of coastal flood vulnerability for compliance with the EU Directive on the Assessment and Management of Flood Risks (2007/60/EC). In this context, a methodology has been created by taking into account three major parameters; the maximum wave run-up modelled from historical weather observations, the highest tide according to historic time series, and the sea level rise projections due to climate change. A high resolution digital terrain model (DTM) derived from LIDAR data has been used to integrate the estimated flood events in a GIS environment. The flood vulnerability map created shows potential risk areas and can play a crucial role in the coastal zone planning process. The proposed method has the potential to be a powerful tool for policy and decision makers for spatial planning and strategic management.

Keywords: coastal floods, vulnerability mapping, climate change, extreme weather events

Procedia PDF Downloads 397

Authors: Corbel Camille, Le Cerf Flora, Capriz Françoise, Vaillant-Ciszewicz Anne-Julie, Breaud Jean, Guerin Olivier, Corveleyn Xavier

Abstract:

Background: The medical environment can generate stressful and anxiety-provoking situations for patients, particularly during painful care procedures for the older population. These stressful environments have deleterious effects on the quality of care and can even put the patient at risk and set the care team up for failure. The search for a solution is, therefore, imperative. The development of new technologies, such as virtual reality (VR), seems to be an answer to this problem. Objectives: The objective of this study is to compare the effects of virtual reality on pain and anxiety when caring for older hospitalized people with the effects of usual care. More precisely, different individual factors (age, cognitive level, individual preferences, etc.) and different virtual reality universes (personalized or non-personalized) are studied to understand the role of these factors in reducing pain and anxiety during care procedures. The aim of this study is to improve the quality of life of patients and caregivers in their work environment. Method: This mono-centered, randomized, controlled study was conducted from September 2023 to September 2024 on 120 participants recruited from the geriatric departments of the Cimiez Hospital, Nice, France. Participants are randomized into three groups: a control group, a personalized VR group and a non-personalized VR group. Each participant is followed during a painful care session. Data are collected before, during and after the care, using measures of pain (Algoplus and numerical scale) and anxiety (Hospital anxiety scale and numerical scale). Physiological assessments with an oximeter are also performed to collect both heart and respiratory rate measurements. The implementation of the care will be assessed among healthcare providers to evaluate its effects on the difficulty and fatigue associated with the care. Additionally, a questionnaire (System Usability Scale) will be administered at the conclusion of the study to determine the willingness of healthcare providers to integrate VR into their daily care practices. Result: The preliminary results indicate significant effects on anxiety (p=.001) and pain (p=<.001) following the VR intervention during care, as compared to the control group. Conclusion: The preliminary results suggest that VRI appears to be a suitable and effective method for reducing anxiety and pain among older hospitalized individuals compared with standard care. Finally, the experiences of healthcare professionals involved will also be considered to assess the impact of these interventions on working conditions and patient support.

Keywords: anxiety, care, pain, older adults, virtual reality

Procedia PDF Downloads 73

Authors: Salsabeel F. M. Alfalah, Jannat F. Falah, Nadia Muhaidat, Amjad Hudaib, Diana Koshebye, Sawsan AlHourani

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Educational technology is changing the way how students engage and interact with learning materials. This improved the learning process amongst various subjects. Virtual Reality (VR) applications are considered one of the evolving methods that have contributed to enhancing medical education. This paper utilizes VR to provide a solution to improve the delivery of the subject of Embryology to medical students, and facilitate the teaching process by providing a useful aid to lecturers, whilst proving the effectiveness of this new technology in this particular area. After evaluating the current teaching methods and identifying students ‘needs, a VR system was designed that demonstrates in an interactive fashion the development of the human embryo from fertilization to week ten of intrauterine development. This system aims to overcome some of the problems faced by the students’ in the current educational methods, and to increase the efficacy of the learning process.

Keywords: virtual reality, student assessment, medical education, 3D, embryology

Procedia PDF Downloads 191

Authors: Anastasia Constantinou, Panayiotis Laouris, Stephen Morris

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Background: Climate change has been reported as one of the worst threats to healthcare. The healthcare sector is a significant contributor to greenhouse gas emissions with primary care being responsible for 23% of the NHS’ total carbon footprint. Digital interventions, primarily focusing on telemedicine, offer a route to change. This systematic review aims to quantify and characterize the carbon footprint savings associated with the implementation of digital interventions in the setting of primary care. Methods: A systematic review of published literature was conducted according to PRISMA (Preferred Reporting Item for Systematic Reviews and Meta-Analyses) guidelines. MEDLINE, PubMed, and Scopus databases as well as Google scholar were searched using key terms relating to “carbon footprint,” “environmental impact,” “sustainability”, “green care”, “primary care,”, and “general practice,” using citation tracking to identify additional articles. Data was extracted and analyzed in Microsoft Excel. Results: Eight studies were identified conducted in four different countries between 2010 and 2023. Four studies used interventions to address primary care services, three studies focused on the interface between primary and specialist care, and one study addressed both. Digital interventions included the use of mobile applications, online portals, access to electronic medical records, electronic referrals, electronic prescribing, video-consultations and use of autonomous artificial intelligence. Only one study carried out a complete life cycle assessment to determine the carbon footprint of the intervention. It estimate that digital interventions reduced the carbon footprint at primary care level by 5.1 kgCO2/visit, and at the interface with specialist care by 13.4 kg CO₂/visit. When assessing the relationship between travel-distance saved and savings in emissions, we identified a strong correlation, suggesting that most of the carbon footprint reduction is attributed to reduced travel. However, two studies also commented on environmental savings associated with reduced use of paper. Patient savings in the form of reduced fuel cost and reduced travel time were also identified. Conclusion: All studies identified significant reductions in carbon footprint following implementation of digital interventions. In the future, controlled, prospective studies incorporating complete life cycle assessments and accounting for double-consulting effects, use of additional resources, technical failures, quality of care and cost-effectiveness are needed to fully appreciate the sustainable benefit of these interventions

Keywords: carbon footprint, environmental impact, primary care, sustainable healthcare

Procedia PDF Downloads 61

Authors: Ulas Cinar, Omer Faruk Ugurlu, Selcuk Cebi

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Occupational safety risk management is the most important element of a safe working environment. Effective risk management can only be possible with accurate analysis and evaluations. Scoring-based risk assessment methods offer considerable ease of application as they convert linguistic expressions into numerical results. It can also be easily adapted to any field. Contrary to all these advantages, important problems in scoring-based methods are frequently discussed. Effective measurability is one of the most critical problems. Existing methods allow experts to choose a score equivalent to each parameter. Therefore, experts prefer the score of the most likely outcome for risk. However, all other possible consequences are neglected. Assessments of the existing methods express the most probable level of risk, not the real risk of the enterprises. In this study, it is aimed to develop a method that will present a more comprehensive evaluation compared to the existing methods by evaluating the probability and severity scores, all sub-parameters, and potential results, and a new scoring-based method is proposed in the literature.

Keywords: occupational health and safety, risk assessment, scoring based risk assessment method, underground mining, weighted risk scores

Procedia PDF Downloads 135

Authors: Osamu Komori, Shinto Eguchi, Hiroshi Okamura, Momoko Ichinokawa

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The long time-series data on population assessments are essential for global ecosystem assessment because the temporal change of biomass in such a database reflects the status of global ecosystem properly. However, the available assessment data usually have limited sample sizes and the ratio of populations with low abundance of biomass (collapsed) to those with high abundance (non-collapsed) is highly imbalanced. To allow for the imbalance and uncertainty involved in the ecological data, we propose a binary regression model with mixed effects for inferring ecosystem status through an asymmetric logistic model. In the estimation equation, we observe that the weights for the non-collapsed populations are relatively reduced, which in turn puts more importance on the small number of observations of collapsed populations. Moreover, we extend the asymmetric logistic regression model using propensity score to allow for the sample biases observed in the labeled and unlabeled datasets. It robustified the estimation procedure and improved the model fitting.

Keywords: double robust estimation, ecological binary data, mixed effect logistic regression model, propensity score

Procedia PDF Downloads 266

Authors: Peter Fedichev

Abstract:

We studied fundamental aspects of aging to develop a mathematical model of gene regulatory network. We show that aging manifests itself as an inherent instability of gene network leading to exponential accumulation of regulatory errors with age. To validate our approach we studied age-dependent omic data such as transcriptomes, metabolomes etc. of different model organisms and humans. We build a computational platform based on our model to identify the targets and biomarkers of aging to design new drugs against aging and age-related diseases. As biomarkers of aging, we choose the rate of aging and the biological age since they completely determine the state of the organism. Since rate of aging rapidly changes in response to an external stress, this kind of biomarker can be useful as a tool for quantitative efficacy assessment of drugs, their combinations, dose optimization, chronic toxicity estimate, personalized therapies selection, clinical endpoints achievement (within clinical research), and death risk assessments. According to our model, we propose a method for targets identification for further interventions against aging and age-related diseases. Being a biotech company, we offer a complete pipeline to develop an anti-aging drug-candidate.

Keywords: aging, longevity, biomarkers, senescence

Procedia PDF Downloads 274