MACHINE LEARNING FOR HEALTHCARE: PREDICTIVE ANALYTICS AND PERSONALIZED MEDICINE

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Om denne e-boken

In the discipline of healthcare informatics, the study of how data relevant to healthcare may be obtained, transmitted, processed, stored, and retrieved is known as the study of how data can be gathered, transferred, processed, stored, and retrieved. In this area of study, early sickness prevention, early illness detection, early illness diagnosis, and early illness therapy are all crucial components. In the subject of healthcare informatics, the only types of data that are considered trustworthy are those that belong to illnesses, patient histories, and the computer operations that are required in order to analyze this data. Conventional medical practices all across the United States have made significant investments in cutting-edge technology and computational infrastructure over the course of the previous two decades in order to improve their potential to support academic institutions, medical experts, and patients. There has been a large investment of resources made in order to increase the quality of medical care that can be provided by utilizing a variety of different options, and this improvement has been made possible as a result of the expenditure. The impetus for all of these numerous programs was the overriding objective of giving patients with access to healthcare that is not only reasonably priced and of excellent quality, but also completely and wholly free of any and all fear. This goal was the driving force behind all of these many programs. As a direct result of these efforts, the benefits and usefulness of applying computational tools to help with referrals and prescriptions, to set up and manage electronic health records (EHR), and to make technical advancements in digital medical imaging have become more obvious. This is particularly the case with regard to electronic health records (EHR), which are becoming increasingly prevalent. This is a direct consequence of the fact that the benefits of utilizing computational tools have been more readily apparent in recent times. With the aid of these technologies, electronic health records (EHR) are something that can be set up and managed.

Om forfatteren

Dr. G. Vishnuvarthanan, born in 1986, is currently working as an Associate Professor, for VIT-Bhopal University, Bhopal, Madhya Pradesh, in the Division of Data Science of School of Computing Science and Education. He has completed his B.E. in Instrumentation Control and Engineering by 2003, followed by M. Tech. In Electronics and Communication Engineering by 2009 and had been awarded a Doctoral Degree in the Department of Electronics and Communication Engineering for the thesis titled “Tumor Detection and Tissue Segmentation in Multimodal MR Brain Images Using Fuzzy and Optimization Techniques” by 2015. He has a total fourteen years of teaching experience in the three different reputed and premier engineering institutes of Tamil Nādu. With more than 100 journal paper publications, to till date he has published 31 international journals indexed in Science Citation Index Database with the highest impact factor publication of 17.560 and an average impact factor of 4.923

Mr. Gunawan Widjaja is a multitalented person. He had a Bachelor in Pharmaceutical Science (BPharm), a Master of Public Health (MPH), and a Master of Hospital Administration (MHA) from the Postgraduate Study Faculty of Public Health, Universitas Indonesia. He also graduated from the Faculty of Law, obtained his LLM, and completed his Doctor of Philosophy (Ph.D.) from the same University. He also holds a Master in Management degree majoring in Finance. Currently, he teaches at the Postgraduate Study Faculty of Public Health Universitas Indonesia and Faculty of Law Universitas Pancasila. He has written about 50 books and many papers in national and international journals, including Scopus Indexed Journals, as well as reviewed them. He actively participated in many seminars, symposiums, and conferences; and also acts as an arbitrator in many International Arbitration centers such as SIAC, SHAC, and GIDI.

Dr. Shahazad Niwazi Qurashi has an extensive background in the field of Computer Science, and Health Informatics. He earned his M.Tech degree from Motilal Nehru National Institute of Technology, Allahabad, and his Ph.D. from Sri Satya Sai University of Technology and Medical Sciences, India. He had more than 14 years of experience in academia and research in various universities including Skyline Institute of Engineering and Technology, AKTU University (Greater Noida, India), MVN University (Palwal, India), and SAMARA University (Ethiopia), Dr .Shahazad is currently employed in the department of Health Informatics, College of Public Health and Tropical Medicine, Jazan University (KSA) and has made significant contributions to the development of healthcare technology where he is working with healthcare professionals to develop innovative solutions for patient care using technology.

Haewon Byeon received the DrSc degree in Biomedical Science from Ajou University School of Medicine. Haewon Byeon currently works at the Department of Medical Big Data, Inje University. His recent interests focus on health promotion, AI-medicine, and biostatistics. He is currently a member of international committee for a Frontiers in Psychiatry, and an editorial board for World Journal of Psychiatry. Also, He were worked on a 4 projects (Principal Investigator) from the Ministry of Education, the Korea Research Foundation, and the Ministry of Health and Welfare. Byeon has published more than 326 articles and 5 books.

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