The Potential of Machine Learning for Improved Diagnostics and Treatment

McDonald, John F.

Title:

The Potential of Machine Learning for Improved Diagnostics and Treatment

dc.contributor.author	McDonald, John F.
dc.contributor.corporatename	Georgia Institute of Technology. Institute for Data Engineering and Science	en_US
dc.contributor.corporatename	Georgia Institute of Technology. School of Biological Sciences	en_US
dc.date.accessioned	2019-06-27T15:13:47Z
dc.date.available	2019-06-27T15:13:47Z
dc.date.issued	2019-06-12
dc.description	Presented on June 12, 2019 at 10:00 a.m. in the Georgia Tech Hotel and Conference Center, Georgia Institute of Technology.	en_US
dc.description	The second-annual Machine Learning in Science and Engineering (MLSE) Conference highlights advances in research that utilize methods of artificial intelligence, the development of new machine learning algorithms designed for science and engineering problems, and the ways these methods lead to innovations across various fields. Researchers from academia, government, and industry will gather to explore the future of research in science and engineering.	en_US
dc.description	PLENARY TALK - John F. McDonald is a professor in the School of Biological Sciences at Georgia Tech, the director of the Integrated Cancer Research Center, and chief scientific officer of the Ovarian Cancer Institute. His research lab takes an integrated systems approach to the study of cancer. They view cancer not as a defect in any particular gene or protein, but as a de-regulated cellular/inter-cellular process. An understanding of such complex processes requires the implementation of experimental approaches that can provide an integrative holistic or “systems” view of intra-and inter-cellular process. They employ a number high-throughput genomic (e.g., DNA-seq, RNA-seq, microarray) technologies to gather systems data on the status of cancer cells. Additionally, they strive to integrate the exceptional strengths that exist at Georgia Tech in the fields of engineering and the computational sciences.	en_US
dc.description	Runtime: 61:48 minutes	en_US
dc.format.extent	61:48 minutes
dc.identifier.uri	http://hdl.handle.net/1853/61462
dc.language.iso	en_US	en_US
dc.publisher	Georgia Institute of Technology	en_US
dc.relation.ispartofseries	IDEaS Conferences
dc.relation.ispartofseries	Machine Learning in Science and Engineering
dc.subject	Diagnostics	en_US
dc.subject	Machine learning	en_US
dc.title	The Potential of Machine Learning for Improved Diagnostics and Treatment	en_US
dc.title.alternative	Machine Learning in Science and Engineering Conference - The Potential of Machine Learning for Improved Diagnostics and Treatment	en_US
dc.type	Moving Image
dc.type.genre	Presentation
dspace.entity.type	Publication
local.contributor.author	McDonald, John F.
local.contributor.corporatename	Institute for Data Engineering and Science
local.relation.ispartofseries	IDEaS Conferences
relation.isAuthorOfPublication	747c573d-7e00-47e6-bd0c-1532a3dfc720
relation.isOrgUnitOfPublication	2c237926-6861-4bfb-95dd-03ba605f1f3b
relation.isSeriesOfPublication	e73bf74b-8831-41fd-b64b-82ce60a15c9f