November 14, 2016 Health and Biotech analytics news roundup

Here’s the latest in health and biotech analytics:

Data Specifics Identified for Prediagnostic Heart Failure Detection: IBM researchers analyzed machine learning models that predict heart failure (paper). Among other findings, they worked out that models perform best with shorter prediction windows.

Will Google Take Over the Medical Industry? Big Questions at CO’s Healthcare Conference: In the keynote speech at the Pulse Healthcare Conference, Andrew Quirk pointed to many new players entering the healthcare industry. Panels at the conference covered topics like patient experiences and the future of hospitals.

Accelerating cancer research with deep learning: Georgia Tourassi is head of Health Data Science at Oak Ridge National Laboratory. Her group is using deep neural networks to extract useful diagnostic data, such as the location of a tumor, from clinical reports.

A student innovation to tackle cognitive challenges in health informatics wins this year’s Sysmex Award: The New Zealand diagnostics company gave the award to Daniel Surkalim, a University of Auckland student. He proposed using “graphical relational integrated databases” to make it easier for providers to access electronic health data.

Originally Posted at: November 14, 2016 Health and Biotech analytics news roundup

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