Description

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The quantification of medical and health care has brought a revolution to our lives with strong and long-lasting social and economic positive impact. This quantification stems from an exemplary synergy among mathematics, statistics, data science, medicine, machine learning (ML) and artificial intelligence (AI), and has been prompting the creation of new interdisciplinary areas across the various fields. While there has been an unprecedented growth and development in many scientific directions, there is a continuing need to further develop existing areas and set the foundations for new ones, as the underlying issues and challenges are evolving in rather complex and interlinked ways. Indeed, creating new therapies has experienced a fast growth already but efficiently funding such innovations and, in turn, making them available at large-scale has its own distinct challenges and demand for new business models and novel decision-making mechanisms. Furthermore, personalized medicine is rapidly becoming a main component of medical care but many issues directly related to the patients’ attitude, risk communication and individual treatment decisions have not been neither extensively studied nor quantified.

The long-term program aims at creating an interdisciplinary platform for knowledge exchange and debate among the various stakeholders: mathematicians, statisticians, physicians, economists, computer scientists, policy makers and researchers in decision science, data science, ML, AI, business, operations research and engineering. The focus will be more on newer interdisciplinary themes like risk management, funding and R&D of biomedical innovation, health care system design, health care delivery, insurance coverage, personalized diagnostics and treatments, telemedicine, medical cyber-physical systems and others.

Organizers

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D B
Donald Berry MD Anderson, Houston
D B
Dimitris Bertsimas MIT
J D
Jing Dong Columbia University
A L
Andrew Lo MIT
A O
Agni Orfanoudaki University of Oxford
M v d S
Mihaela van der Schaar University of Cambridge
T Z
Thaleia Zariphopoulou University of Texas at Austin