Plenary Keynote Presentation & Keynote Sessions
4:35 – 6:00 pm
The use of artificial intelligence, and the deep-learning subtype, in particular, has been enabled by the use of labeled big data, along with markedly enhanced computing power and cloud storage, across all sectors. In medicine, this is beginning to have an impact at three levels: for clinicians, predominantly via rapid, accurate image interpretation; for health systems, by improving workflow and the potential for reducing medical errors; and for patients, by enabling them to process their own data to promote health. The current limitations, including bias, privacy and security, and lack of transparency, along with the future directions of these applications will be discussed in this article. Over time, marked improvements in accuracy, productivity, and workflow will likely be actualized, but whether that will be used to improve the patient–doctor relationship or facilitate its erosion remains to be seen.
Eric Topol, MD, Founder and Director, Scripps Research Translational Institute (SRTI); Author, Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again
3:15 – 4:50 pm
What Does the New Era of Genomic Medicine Look Like? Effects on Patient Care, Therapeutics, and Diagnostics
Kevin Davies, PhD, Executive Editor, The CRISPR Journal, Mary Ann Liebert, Inc.
Stephen Kingsmore, MD, DSc, President/CEO, Rady Children’s Institute for Genomic Medicine
David Haussler, PhD, Investigator, Howard Hughes Medical Institute; Distinguished Professor, Biomolecular Engineering, University of California, Santa Cruz; Scientific Director, UC Santa Cruz Genomics Institute; Scientific Co-Director, California Institute for Quantitative Biosciences (QB3)
Elizabeth Worthey, PhD, Director, Genomic Medicine, University of Alabama, Birmingham School of Medicine
8:00 – 9:40 am
Pragmatic Use of Informatics in Cancer Care Delivery and Cancer Research: Big Data and AI Take on Cancer
In oncology today, increasingly large amounts of heterogeneous data, created by multiple medical disciplines, is being collected and aggregated and technologies such as machine learning and deep learning are being tested to create knowledge and insight to improve cancer care and inform oncology research and drug discovery. This panel will bring together many of the stakeholders to discuss the challenges and opportunities in using big data and informatics tools to improve cancer care delivery and cancer research. This panel will include practicing oncologists, oncology researchers, machine learning experts, payers, pharmaceutical and translational researchers and technology solution providers.
Topics to include:
- The value and application of informatics in research and in practical cancer care delivery
- Predictive analytics to improve risk stratification in oncology
- State of comprehensive genomic profiling in oncology
- Aggregation and analysis of genomic and patient reported outcome data
- Aggregation and analysis of patient records, population level analysis and building cohorts of patients
- Translational research and Informatics tools in support of clinical trials
- Big data from recurrence and resistance, informing identification of new targets and driving new drug discovery campaigns
- Transforming cancer, diagnosis, drug discovery and patient care with Big Data and AI
- Reproducible research, data conformance and semantic modeling
Joseph Ferrara, CEO, Boston Healthcare
Mark Hulse, Chief Digital Officer, City of Hope
Ajay Shah, PhD, Executive Director & Head of IT for Translational Medicine, Bristol-Myers Squibb
* The program is subject to change without notice, due to unforeseen reason.