Artificial Intelligence and Machine Learning in Health Care and Medical Sciences: Best Practices and Pitfalls

Author:   Gyorgy J. Simon ,  Constantin Aliferis
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2024
ISBN:  

9783031393570


Pages:   810
Publication Date:   05 March 2024
Format:   Paperback
Availability:   In Print   Availability explained
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Artificial Intelligence and Machine Learning in Health Care and Medical Sciences: Best Practices and Pitfalls


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Author:   Gyorgy J. Simon ,  Constantin Aliferis
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2024
ISBN:  

9783031393570


ISBN 10:   3031393570
Pages:   810
Publication Date:   05 March 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Dr. Gyorgy Simon earned his PhD in Computer Science with a minor in Statistics from the University of Minnesota. Subsequently, he was a senior software engineer at Yahoo! Search Engine Technologies and later joined Mayo Clinic where he developed clinical data mining techniques, before joining the University of Minnesota He is a federally-funded investigator with extensive experience developing and applying AI and ML methods in a variety of application settings. He is currently a tenured Associate Professsor in the Institute for Health Informatics with additional appointments in Medicine and Data Science.  Constantin Aliferis received an MD degree from Athens University in Greece in 1990, and an MS in 1994 and PhD in 1998 in Artificial Intelligence from the University of Pittsburgh. He also completed a post doctoral Fellowhip focusing on Machine Learning in Biomedicine. His has served as faculty in Biomedical Informatics, Computer Science, Biostatistics and Cancer Biology at Vanderbilt University; Informatics, Computational Biology, Data Science and Pathology at NYU; and Informatics, Medicine and Data Science at the University of Minnesota. He has also been a regular faculty member in the Cancer Centers of the above universities and architected/led their MS and PhD programs in Biomedical Informatics. He has also been the director of the NYU’s Center for Health Informatics and Bioinformatics, and Director of the UMN Institute for Health Informatics at the UMN where he is also Chief Research Informatics Officer and a tenured Professor. He is a federally-funded investigator who has pioneered several novel and best-of-breed AI and ML methods, applied them in dozens of areas, and has also published extensively in method benchmarking and several other best-practice-related topics.

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