Overview

Data Science in the Medical Field focuses on the potential tools that can be used in data science to identify signs of illness at extremely early stages. Today's rapid advancements in data science provide the potential to influence and improve fundamental services in the healthcare sector, including many important applications across the healthcare spectrum. As every human body produces two terabytes of data each day, including brain activity, stress level, heart rate, blood sugar level, and many other data points, this book discusses how data science can help clinicians and researchers handle the massive volume of data to better track patient health.

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Seifedine Kadry is a professor at Noroff University College, in Norway. At present, his research focuses on data Science, education using technology, system prognostics, stochastic systems, and applied mathematics. He is an ABET program evaluator for computing, and ABET program evaluator for Engineering Tech. He is a Fellow of IET, Fellow of IETE, and Fellow of IACSIT. He is a distinguished speaker of IEEE Computer Society. Dr Shubham Mahajan is a member of the IEEE, ACM and IAENG; Dr Mahajan is pursuing a post-doctoral degree in the Department of Applied Data Science at Noroff University College in Kristiansand, Norway. He is Visiting Assistant Professor in the Department of Communication and Computer Engineering at Al-Ahliyya Amman University in Jordan. His research interests span a wide array of topics, encompassing: image processing, video compression, image segmentation, fuzzy entropy, nature-inspired computing methods, optimization, data mining, machine learning, robotics, and optical communication. His publications include: “Innovations in Biomedical Engineering: Trends in Scientific Advances and Applications”, published with Elsevier

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