Machine Intelligence for Healthcare. Questo articolo non è disponibile.Machine Intelligence for Healthcare

Machine Intelligence for Healthcare is a must read for physician leaders, health insurance executives, clinical researchers, public health officials, data scientists and software engineers seeking to understand this pivotal innovation in the information revolution in healthcare.  MI for Healthcare provides a detailed introduction of Machine Intelligence, then takes the reader on a journey through the basics of machine learning, topological data analysis and applications of machine intelligence software for healthcare and life sciences. Over 20 case studies cover topics related to clinical variation analysis, hospital clinical pathways, population health management, genetic analysis, precision medicine, healthcare revenue cycle, and payment integrity. The book includes a detailed introduction of the mathematics of topology and concepts of machine learning algorithms. This provides an understanding for the central role which machine intelligence software is now playing in the emergence of the "learning healthcare system" and success in the new world of value-based healthcare delivery.

Gunnar Carlsson is a Professor of Mathematics (emeritus) at Stanford University, and one of the founders of Ayasdi, which is commercializing products based on machine intelligence and topological data analysis. His career has been devoted to the study of topology, the mathematical study of shape. He has taught at University of Chicago, University of California (San Diego), Princeton University, and since 1991 at Stanford University. He has served as the Chair of the Mathematics department at Stanford, is the author of over 100 academic papers, and has given numerous addresses to scholarly meetings. His work on the applications of topology to the analysis of large and complex data sets has led to a number of projects, notably a multi-university initiative funded by the Defense Advanced Research Projects Agency during the period 2005-2010. He is a founder of the ATMCS series of conferences focusing on the applications of topology, and is a founding editor of the Journal for Applied and Computational Topology. He received the B.A. in mathematics from Harvard in 1973, and the Ph.D., in mathematics from Stanford in 1976. Francis “FX” Campion serves as the Chief Medical Officer for Ayasdi, providing leadership for machine intelligence solutions for healthcare and life sciences. He has devoted his career to patient care, research and clinical informatics. He has led electronic health record implementation and optimization efforts for medical groups and hospitals. His research focuses on the secondary use of healthcare data for patient safety and clinical effectiveness. FX has held leadership roles at Dovetail Health (acquired by Optum), Alere Analytics, Outcome Sciences (acquired by Quintiles), Atrius Health, Caritas Christi, and Lahey Clinic. FX has practiced internal medicine for over 25 years, now with Harvard Vanguard Medical Associates in Boston, MA. He is board certified in both internal medicine and clinical informatics. He is an instructor in the Department of Population Medicine and mentor in the Center for Primary Care at Harvard Medical School. Dr. Campion received his medical degree from Harvard Medical School in 1987 and completed internal medicine residency at New England Deaconess Hospital. He has an undergraduate degree from the College of the Holy Cross.