Artificial Intelligence for Healthcare Applications and Management

Dr. Boris Galitsky has contributed linguistic and machine learning technologies to Silicon Valley startups as well as companies like eBay and Oracle for over 25 years. Dr. Galitsky’s information extraction and sentiment analysis techniques assisted several acquisitions, such as Xoopit by Yahoo, Uptake by Groupon, Log logic by Tibco and Zvents by eBay. His security-related technologies of document analysis contributed to the acquisition of Elastica by Semantec. As an architect of the Intelligent Bots project at Oracle, Dr. Galitsky 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 Apache committer to OpenNLP where he created OpenNLP. Similarity component which 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 autistic reasoning 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.

1. Introduction Boris Galitsky 2. Multi-case-based reasoning by syntactic-semantic alignment and discourse analysis Boris Galitsky 3. Obtaining supported decision trees from text for health system applications Boris Galitsky 4. Search and prevention of errors in medical databases Saveli Goldberg 5. Overcoming AI applications challenges in health: Decision system DINAR2 Saveli Goldberg and Mark Prutkin 6. Formulating critical questions to the user in the course of decision–making Boris Galitsky 7. Relying on discourse analysis to answer complex questions by neural machine reading comprehension Boris Galitsky 8. Machine reading between the lines (RBL) of medical complaints Boris Galitsky 9. Discourse means for maintaining a proper rhetorical flow Boris Galitsky 10. Dialogue management based on forcing a user through a discourse tree of a text Boris Galitsky 11. Building medical ontologies relying on communicative discourse trees Boris Galitsky and Dmitry Ilvovsky 12. Explanation in medical decision support systems Saveli Goldberg 13. Passive decision support for patient management Saveli Goldberg and Stanislav Belyaev 14. Multimodal discourse trees for health management and security Boris Galitsky 15. Improving open domain content generation by text mining and alignment Boris Galitsky