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BD2K Standards Coordinating Center: Ilya Goldberg, PhD
June 23, 2016 @ 1:00 pm - 2:00 pm
Imaging Ontologies, Big Data and Machine Learning:
The Path to Better Healthcare
Head of the Image Informatics and Computational Biology Unit (IICBU) at the National Institute on Aging
United States: 1(415) 655-0002 | Access Code: 730 883 855
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Abstract: Big Data is the application of modern analytical tools like machine learning to large data collections to extract information hidden from even expert observers. Because the process is more data driven than hypothesis based, ontologies and structured meta-data are critical for describing these datasets in machine-readable ways. The convergence of both of these technologies at the intersection of imaging data and healthcare poses an extreme challenge as well as potential benefit. Several case studies will be presented where machine learning and pattern recognition was applied to medical imaging and clinical data to give us new insights that could not have been otherwise gained in any conventional way.
Biography: Dr. Ilya Goldberg: Dr. Goldberg is the head of the Image Informatics and Computational Biology Unit (IICBU) at the National Institute on Aging (part of NIH) where he develops software and standards for Open Microscopy Environment (OME: http://openmicroscopy.org), new approaches to pattern recognition in images, and new technology for image-based high throughput screening. All of this technology development drives the central theme of the IICBU: How cell and tissue morphology relate to cellular and organismal state. In 1999, while a post-doc in image informatics at MIT, he co-founded the OME, a database framework for archiving, sharing and analyzing scientific images. OME was the first example of a scalable infrastructure for high-throughput scientific imaging, and it continues to be developed by an international consortium as well as being used by industry in commercial products, and research groups using high-throughput imaging and image informatics in their biological research.