JUN 21, 2018 9:00 AM PDT

Can AI Beat Cancer?

Speaker

Abstract

Finding effective treatments for cancer is fundamentally  a high-dimensional probabilistic planning, search, and optimization problem, characterized by  thousands of molecular subtypes,  tens of thousands of plausible drug regimens, and a dearth of high quality data on clinical responses.  These explosive combinatorics and the lack of data are overwhelming traditional approaches to clinical development, including the latest Bayesian adaptive trial designs and big data analytics.  However, this is precisely the kind of knowledge-based  planning and search problem that AI is uniquely designed to solve.  Many organizations are developing relevant AI-based applications, from decision support and treatment planning to treatment validation and real time response monitoring.  We will review these developments and describe a bold industry-wide initiative to integrate them for the immediate benefit of all cancer patients and their physicians, while radically improving the efficiency of clinical research and drug development. 


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JUN 21, 2018 9:00 AM PDT

Can AI Beat Cancer?


Specialty

Cancer Diagnostics

Cancer Research

Gene Sequencing

Personalized Medicine

Cancer

Dna Sequencing

Clinical Diagnostics

Big Data

Biomarkers

Tumor

Publishing

Earth Science

Flow Cytometry

University

Immuno-Oncology

Geography

North America50%

Asia25%

Europe25%

Registration Source

Website Visitors100%

Job Title

Student33%

Research Scientist33%

Medical Laboratory Technician33%

Organization

Hospital25%

Manufacturer - Other25%

Academic Institution25%

Clinical Laboratory25%


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