Applications of AI and HPC in the Health Domain

2022 ◽  
pp. 217-239
Author(s):  
Dana Oniga ◽  
Barbara Cantalupo ◽  
Enzo Tartaglione ◽  
Daniele Perlo ◽  
Marco Grangetto ◽  
...  
Keyword(s):  
Health Domain ◽  
Applications Of Ai

A survey on cloud computing privacy and security compliances in health domain (Preprint)

2020 ◽  
Author(s):  
Zahra Zandesh
Keyword(s):  
Cloud Computing ◽  
New Paradigm ◽  
Data Governance ◽  
Healthcare Organizations ◽  
Privacy And Security ◽  
Memory Space ◽  
Health Domain ◽  
Security Services ◽  
Cloud Compliance ◽  
Complicated Nature

BACKGROUND The complicated nature of cloud computing encompassing internet-based technologies and service models for delivering IT applications, processing capability, storage, and memory space and some notable features motivate organizations to migrate their core businesses to the cloud. Consequently, healthcare organizations are much interested to migrate to this new paradigm despite challenges about security, privacy and compliances issues. OBJECTIVE The present study was conducted to investigate all related cloud compliances in health domain in order to find gaps in this context. METHODS All works on cloud compliance issues were surveyed after 2013 in health domain in PubMed, Scopus, Web of Science, and IEEE Digital Library databases. RESULTS Totally, 36 compliances had been found in this domain used in different countries for a variety of purposes. Initially, all founded compliances were divided into three parts as well as five standards, twenty-eight legislations and three policies and guidelines each of which is presented here by in detail. CONCLUSIONS Then, some main headlines like compliance management, data management, data governance, information security services, medical ethics, and patients' rights were recommended in terms of any compliance or frameworks and their corresponding patterns which should be involved in this domain.

scholarly journals Quality of life of schizophrenic patients in a tertiary care hospital in Bangladesh

2017 ◽  
Vol 29 (1) ◽  
pp. 30-34 ◽  
Author(s):  
Mir Hasan Shakil Mahmud ◽  
Bushra Yeasmin ◽  
Shipra Mandal
Keyword(s):  
Quality Of Life ◽  
Physical Health ◽  
Environmental Health ◽  
Social Relationship ◽  
World Health ◽  
P Value ◽  
Health Domain ◽  
Schizophrenic Patients ◽  
Physical Health Domain

Schizophrenia is one of the major mental disorders which affect individual’s thinking ability, social interaction or attention. It affects person’s entire quality of life. The purpose of the study was to find out the quality of life of schizophrenic patient in Bangladesh. Cross sectional study design was used to conduct this study. The convenient sampling procedure was used throughout the process of participant’s selection and the numbers of respondents were 83. The study was carried out at National Institute of Mental Health and Hospital (NIMH), Dhaka. Data was collected by using face to face interview with a structured questionnaire WHOQOL-BREF (The World Health Organization Quality of Life- BREF) scale. It was found that most of the participants lead poor to moderate quality of life in four domains of the WHOQOL-BREF scale. Results showed that mean scores were for physical health (mean 2.7, SD+0.106); psychological health (mean 2.108, SD +0.0787); social relationship (mean 2.226; SD+0.116) and environmental health (mean 2.47; SD+0.077).This study indicated that, quality of life poor on psychological domain. It was also found statistically significance with age and social relationship domain (p value 0.005< 0.05); marital status and physical health domain (p value 0.004<0.05); educational level and physical health domain (p value 0.005<0.05) and environmental health domain (p value 0.025<0.05). There were no statistically significant difference between gender and other variables. Schizophrenia affects all aspects of person’s life such as physically, psychologically, socially and economically. Schizophrenic patients as well as their family members led very poor quality of life.Bang J Psychiatry June 2015; 29(1): 30-34

Sports Medicine and Artificial Intelligence: A Primer

2021 ◽  
pp. 036354652110086
Author(s):  
Prem N. Ramkumar ◽  
Bryan C. Luu ◽  
Heather S. Haeberle ◽  
Jaret M. Karnuta ◽  
Benedict U. Nwachukwu ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Sports Medicine ◽  
Injury Risk ◽  
Industrial Revolution ◽  
Improve Patient Care ◽  
Great Promise ◽  
Patient Reported ◽  
Athlete Injury ◽  
Improve Patient ◽  
Applications Of Ai

Artificial intelligence (AI) represents the fourth industrial revolution and the next frontier in medicine poised to transform the field of orthopaedics and sports medicine, though widespread understanding of the fundamental principles and adoption of applications remain nascent. Recent research efforts into implementation of AI in the field of orthopaedic surgery and sports medicine have demonstrated great promise in predicting athlete injury risk, interpreting advanced imaging, evaluating patient-reported outcomes, reporting value-based metrics, and augmenting the patient experience. Not unlike the recent emphasis thrust upon physicians to understand the business of medicine, the future practice of sports medicine specialists will require a fundamental working knowledge of the strengths, limitations, and applications of AI-based tools. With appreciation, caution, and experience applying AI to sports medicine, the potential to automate tasks and improve data-driven insights may be realized to fundamentally improve patient care. In this Current Concepts review, we discuss the definitions, strengths, limitations, and applications of AI from the current literature as it relates to orthopaedic sports medicine.

scholarly journals Radiology Community Attitude in Saudi Arabia about the Applications of Artificial Intelligence in Radiology

Healthcare ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 834
Author(s):  
Magbool Alelyani ◽  
Sultan Alamri ◽  
Mohammed S. Alqahtani ◽  
Alamin Musa ◽  
Hajar Almater ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Saudi Arabia ◽  
Vital Role ◽  
Human Machine Interaction ◽  
The Future ◽  
Level Of Knowledge ◽  
Electronic Questionnaires ◽  
Machine Interaction ◽  
Applications Of Ai

Artificial intelligence (AI) is a broad, umbrella term that encompasses the theory and development of computer systems able to perform tasks normally requiring human intelligence. The aim of this study is to assess the radiology community’s attitude in Saudi Arabia toward the applications of AI. Methods: Data for this study were collected using electronic questionnaires in 2019 and 2020. The study included a total of 714 participants. Data analysis was performed using SPSS Statistics (version 25). Results: The majority of the participants (61.2%) had read or heard about the role of AI in radiology. We also found that radiologists had statistically different responses and tended to read more about AI compared to all other specialists. In addition, 82% of the participants thought that AI must be included in the curriculum of medical and allied health colleges, and 86% of the participants agreed that AI would be essential in the future. Even though human–machine interaction was considered to be one of the most important skills in the future, 89% of the participants thought that it would never replace radiologists. Conclusion: Because AI plays a vital role in radiology, it is important to ensure that radiologists and radiographers have at least a minimum understanding of the technology. Our finding shows an acceptable level of knowledge regarding AI technology and that AI applications should be included in the curriculum of the medical and health sciences colleges.

scholarly journals Trust me; I know what I am doing investigating the effect of choice list elicitation and domain-relevant training on preference reversals in decision making for others

2021 ◽  
Author(s):  
Sebastian Neumann-Böhme ◽  
Stefan A. Lipman ◽  
Werner B. F. Brouwer ◽  
Arthur E. Attema
Keyword(s):  
Decision Making ◽  
Economic Theory ◽  
Medical Students ◽  
Practical Problem ◽  
Applied Research ◽  
Significant Problem ◽  
Preference Reversals ◽  
Health Domain ◽  
Economics Students ◽  
Financial Domain

AbstractOne core assumption of standard economic theory is that an individual’s preferences are stable, irrespective of the method used to elicit them. This assumption may be violated if preference reversals are observed when comparing different methods to elicit people’s preferences. People may then prefer A over B using one method while preferring B over A using another. Such preference reversals pose a significant problem for theoretical and applied research. We used a sample of medical and economics students to investigate preference reversals in the health and financial domain when choosing patients/clients. We explored whether preference reversals are associated with domain-relevant training and tested whether using guided ‘choice list’ elicitation reduces reversals. Our findings suggest that preference reversals were more likely to occur for medical students, within the health domain, and for open-ended valuation questions. Familiarity with a domain reduced the likelihood of preference reversals in that domain. Although preference reversals occur less frequently within specialist domains, they remain a significant theoretical and practical problem. The use of clearer valuation procedures offers a promising approach to reduce preference reversals.

Welcome to AI Matters 7(1)

AI Matters ◽  
2021 ◽  
Vol 7 (1) ◽  
pp. 4-4
Author(s):  
Iolanda Leite ◽  
Anuj Karpatne
Keyword(s):  
High School Students ◽  
Regular Education ◽  
Physical World ◽  
School Students ◽  
Social Good ◽  
The Third ◽  
Ai Ethics ◽  
K 12 ◽  
Applications Of Ai

Welcome to the first issue of this year's AI Matters Newsletter! We start with a report on upcoming SIGAI Events by Dilini Samarasinghe and Conference reports by Louise Dennis, our conference coordination officers. In our regular Education column, Duri Long, Jonathan Moon, and Brian Magerko introduce two "unplugged" activities (i.e., no technology needed) to learn about AI focussed on K-12 AI Education. We then bring you our regular Policy column, where Larry Medsker covers several topics on AI policy, including the role of Big Tech on AI Ethics and an interview with Dr. Eric Daimler who is the CEO of the MIT-spinout Conexus.com. Finally, we close with four article contributions. The first article discusses emerging applications of AI in analyzing source code and its implications to several industries. The second article discusses topics in the area of physical scene understanding that are necessary for machines to perceive, interact, and reason about the physical world. The third article presents novel practices and highlights from the Fourth Workshop on Mechanism Design for Social Good. The fourth article provides a report on the "Decoding AI" event that was conducted online by ViSER for high school students and adults sponsored by ACM SIGAI.

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