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Demystifying Medicine 2019 - Machine Learning and Artificial Intelligence in Radiology

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Air date: Tuesday, March 12, 2019, 4:00:00 PM
Time displayed is Eastern Time, Washington DC Local
Views: Total views: 347, (170 Live, 177 On-demand)
Category: Demystifying Medicine
Runtime: 01:26:01
Description: Demystifying Medicine Lecture Series

Robots don't write these Demystifying Medicine messages, but they may in the near future…with fewer grammatical errors. Artificial intelligence (AI), machine learning (ML), and deep learning (DL) are poised to master mundane and rote tasks and perform them with efficiencies far greater than what can be done by humans. AI refers to computerized tasks that have elements of human smartness, or decision-making, as opposed to raw computing and number-crunching; ML is a subset of AI in which the computer system learns new tasks without additional programming. DL is ML on computer steroids, utilizing powerful computers and massive datasets to deduce features in the data and to establish and then refine computational rules to identify objects.

We bring you two speakers who are using AI, ML, and DL in a clinical setting to save lives and enhance patient safety and care. Ron Summers is chief of the Clinical Center's Clinical Image Processing Service and directs the Imaging Biomarkers and Computer-Aided Diagnosis Laboratory. Among many accomplishments, his group has applied DI techniques to create a dataset of 120,000 anonymized chest X-rays that researchers worldwide now can use to identify disease and abnormalities in their own patients' X-rays.

Co-presenter Baris Turkbey, a physician in the NCI Molecular Imaging Program is applying similar technology to the field of prostate cancer, in which imaging has been a challenging task because of the high variability of the prostate anatomic structure. The robots are rapidly outperforming the human experts in identifying abnormalities reviewed by the imaging!

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Author: Ronald Summers, MD, PhD, CC, NIH and Baris Turkbey, MD, NCI, NIH
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CIT Live ID: 30278
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