MACHINE LEARNING IN HEALTH CARE DIAGNOSIS AND PROGNOSIS

Bhargavi Posinasetty · Dr. Aadam Quraishi MD · Dr. Vikas Malgotra · Mr. Dayakar Babu Kancherla

Dec 2023 · Xoffencerpublication

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268

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About this ebook

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. The only kinds of data that are regarded credible in the field of healthcare informatics are those that pertain to diseases, patient histories, and the computer operations that are necessary in order to analyze this data. Over the course of the past two decades, conventional medical practices across the United States have made major investments in cutting-edge technical and computational infrastructure in order to enhance their capacity to provide assistance to academics, medical professionals, and patients. There has been a significant investment of resources made in order to improve the level of medical care that may be offered by utilizing these various. The motivation for all of these many programs was the overarching goal of providing patients with access to healthcare that is not only affordably priced and of high quality, but also totally and entirely free of any and all fear. As a direct result of these efforts, the benefits and relevance of employing computational tools to aid with referrals and prescriptions, to set up and maintain electronic health records (EHR), and to make technical improvements in digital medical imaging have been clearer. This is a direct result of the fact that the advantages of applying computational tools have become more obvious. Electronic health records (EHR) are something that can be set up and managed with the assistance of these technologies. It has been demonstrated that computerized physician order entry, more frequently referred to as CPOE, may be able to increase the quality of care that is delivered to patients while

About the author

Bhargavi Posinasetty is a seasoned professional with over 7 years of expertise in clinical trials and data management. Holding a Master’s in Public Health (MPH) with a specialization in Epidemiology & Biostatistics from The University of Southern Mississippi, MS, and a Bachelor of Dental Surgery in General Dentistry from Rajiv Gandhi University of Health Sciences, India, Bhargavi uniquely combines healthcare and research in her career.

Dr. Aadam Quraishi MD, MBA has research and development roles involving some combination of NLP, deep learning, reinforcement learning, computer vision, predictive modeling. He is actively leading team of data scientists, ML researchers and engineers, taking research across full machine learning life cycle - data access, infrastructure, model R&D, systems design and deployment.

Dr. Vikas Malgotra is working as a Senior Resident in Dermatology at GMC, Udhampur. He holds an MD in Dermatology from GMC, Jammu and believes in evidence-based practice of medicine. He likes to research, write, and stay updated about the advances and techniques to optimize skin health and general well-being. With a keen interest in dermatology, mycology, and dermatopathology, Vikas has made significant contributions to the field. Over the course of his academic and professional journey, Vikas has authored 6 publications in indexed journals, presenting 5 posters at national conferences. In addition to his research papers, he has penned a pivotal book on "Food Allergies," which delves deep into the world of food allergies, offering readers a comprehensive understanding of the subject.

Mr. Dayakar Babu Kancherla is a Technology Leader and currently works as Engineering Manager from Plano, Texas. He has vast experience in technology including but not limited to System Design, Cloud, Devops, Site Reliability Engineering, IT Operations, Security Ops. He is currently working on Digitizing health, Pharmacy experiences for one of the major retail chain in US and Canada. He has multiple patents published in the field of Digitizing health, AI/ML and Data Science. He has about more than a decade experience mentoring engineers, researchers and been a judge in technical hackathon. He has been a IEEE senior member and published international papers in the field of health diagnosis, Data analytics, Generative AI and Machine Learning

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