Artificial Intelligence for Healthcare Applications and Management...
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About the book
Collection
n.c
Publication date
2022-01-13
Pages
548 pages
Print ISBN
9780128245217
Language
English
Ebook informations
EAN EPUB DRM-FREE
9780128245224
Price
£121.32
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Dr. Boris Galitsky is a cofounder of Knowledge Trail, San Jose, CA. He has contributed linguistic and machine learning technologies to Silicon Valley start-ups as well as companies such as eBay and Oracle for over 25 years. His information extraction and sentiment analysis techniques assisted several acquisitions, such as Xoopit by Yahoo, Uptake by Groupon, LogLogic by Tibco, and Zvents by eBay. His security-related technologies of document analysis contributed to the acquisition of Elastica by Symantec. As an architect of the Intelligent Bots project at Oracle, he developed a discourse analysis technique used for dialogue management and published in the book Developing Enterprise Chatbots. He also published a two-volume monograph "AI for CRM, based on his experience developing Oracle Digital Assistant. He is an Apache committer to OpenNLP where he created OpenNLP. Similarity component that is a basis for a semantically enriched search engine and chatbot development. Dr. Galitsky's exploration and formalization of human reasoning culminated in the book Computational Autism broadly used by parents of children with autism and rehabilitation personnel. His focus on the medical domain led to another research monograph, Artificial Intelligence for Healthcare Applications and Management, co-authored with Dr. Saveli Goldberg.Dr. Saveli Goldberg has contributed biostatistics and machine learning technologies to research at Harvard Medical School and Massachusetts General Hospital for the last 20 years, where he is currently a biostatistician and data analyst. The author of more than 80 publications and 2 patents, he is currently researching several projects in the field of radiation oncology and endocrinology. The main areas of his research include (a) optimal strategies in cancer radiation therapy, (b) optimal targets and strategies in the treatment of diabetes and hypertension, (c) the optimal combination of expert and artificial intelligence to get the right solution, (d) explanation of the machine learning solution, and (e) the relationship of electronic documentation to patient outcomes.

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