MACHINE LEARNING IN HEALTHCARE

Dr. Anand Ashok Khatri · Dr. Ashok Kumar · Miss. Namrata Gohel · Renato Racelis Maaliw III

jun. 2023 · Xoffencerpublication

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The study of how data pertaining to healthcare may be gathered, transferred, processed, stored, and retrieved is what is known as the field of healthcare informatics. Early illness prevention, early disease detection, early disease diagnosis, and early disease therapy are all essential components of this field of research. Within the realm of healthcare informatics, the only types of data that are considered reliable are those that pertain to illnesses, patient histories, and the computing procedures that are required to interpret this data. Conventional medical practices throughout the United States have made significant investments in state-of-the-art technological and computational infrastructure over the course of the last two decades in order to improve their ability to support academics, medical professionals, and patients. Significant resources have been invested in order to raise the quality of medical treatment that can be provided by using these approaches. The aim to offer patients with healthcare that is not only reasonably priced and of good quality, but also completely free of any and all anxiety served as the impetus for these many projects. As a direct result of these efforts, the advantages and significance of utilizing computational tools to help with referrals and prescriptions, to set up and manage electronic health records (EHR), and to make technological advancements in digital medical imaging have become more obvious. These tools can also assist with setting up and managing electronic health records (EHR). It has been shown that computerized physician order entry, commonly known as CPOE, may improve the quality of care that is provided to patients while simultaneously lowering the number of prescription mistakes and adverse drug reactions. When a doctor uses CPOE, they are able to swiftly get pertinent patient data without having to leave the screen where they are entering prescriptions. The history of the patient provides the treating physician with advance notice of any possibly dangerous responses. Moreover, the CPOE offers the physician the ability to monitor the order's development as it moves through the system.

Om forfatteren

Dr. Anand Ashok Khatri holds a Bachelor of Engineering in Computer Engineering and Master of Engineering in Computer Engineering from Savitribai Phule Pune University, Pune, Maharashtra in India and a Ph.D. in Computer Engineering from Shri Jagdishprasad Jhabarmal Tibrewala University, University in Jhunjhunu, Rajasthan (JJTU), India (2022). The Computer Engineering, Jaihind College of Engineering Kuran Pune Maharashtra in India are where he presently serves as an Associate Professor. For a total of 22 years during his career, he has worked as a full-time professor. He is the Head of Computer Engineering and Artificial Intelligence & Data Science Department. He has a background in computer engineering, with a focus on Data Science, Artificial Intelligence, Machine Learning Cognitive Radio Network, Computer Networks and Information Security. He has published research papers in both national and international journals, and is a life time membership of India Society for Technical Education (ISTE).

Dr. Ashok Kumar working as an Assistant Professor in the Department of Computer Science, Banasthali Vidyapith, Banasthali-304022 (Rajasthan), has about 14 years of teaching experience. He received his M.C.A. degree from GJU University, M.Phil. degree in Computer Science from CDLU University and Ph.D. degree in Computer Science from Banasthali Vidyapith. He has more than 25 research papers in refereed international journals, conferences and three patents in his credit. His areas of research include Image Processing, Machine Learning and Big Data Analytics.

Miss. Namrata Gohel is an Assistant Professor in the Department of Computer Engineering at Ahmedabad Institute of Technology, Gujarat. Miss. Namrata has 5 years of Experience as an active academician and researcher also. She has published papers in various reputed journals.

Renato Racelis Maaliw III is an Associate Professor and currently the Dean of the College of Engineering in Southern Luzon State University, Lucban, Quezon, Philippines. He has a doctorate degree in Information Technology with specialization in Machine Learning, a Master's degree in Information Technology with specialization in Web Technologies, and a Bachelor’s degree in Computer Engineering. His area of interest is in computer engineering, web technologies, software engineering, data mining, machine learning, and analytics. He has published original researches, a 7-time best paper awardee for various IEEE sanctioned conferences; served as technical program committee for IEEE conferences, peer reviewer for reputable journals

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