Topic: Artificial Intelligence / Machine Learning

In partnership with the National Cancer Institute (NCI) Cancer Moonshot^SM, the Society for Immunotherapy of Cancer (SITC) and the Big Data and Data Sharing Committee are excited to announce our second “SITC-NCI Computational Immuno-Oncology Webinar Series” throughout 2022.

These nine, hour-long webinars will feature a moderator and faculty speaker leading instruction on a range of topics that cover a host of computational challenges of analyzing and integrating diverse assay data across the spectrum of immuno-oncology. Meant for scientists early in their career or those who want to remain abreast of the latest technologies, the goal of this series is to help foster better communication concerning data science technologies and analyses between cancer immunotherapy researchers and clinicians in order to fuel translational immunotherapy research.

Join University of Colorado’s Dr. Arjun Krishnan as he discusses how machine learning and natural language processing can contribute to making public -omics data more accessible.

Dr. Krishnan will also present the recent work from his group, the Krishnan Lab, to address these two challenges that contribute to under-used data:

• Unstructured metadata: sample descriptions contain information about their source in the form of ambiguous plain text.
• Missing metadata: sample descriptions frequently miss key, basic pieces of information about their source.

The Krishnan Lab works in the areas of computational biology and biomedical data science at the University of Colorado Anschutz Medical Campus.

The Data Science Seminar Series presents talks from innovators in the cancer research and informatics communities both within and outside of NCI.

Speaker:

Arjun Krishnan, Ph.D.

Dr. Krishnan is an associate professor at the University of Colorado and a group leader at the Krishan Lab. He works on developing computational approaches to study the genetic basis of biomedical phenomena relevant to human health and disease. Dr. Krishnan is primarily interested in bridging the gap between large-scale genomic/clinical data and actionable biological insights using statistical and machine learning approaches.

In this seminar, Project Rōnin’s Vice President of Data Science, Dr. Christine Swisher, will discuss the challenges of ensuring safe and ethical artificial intelligence (AI) in healthcare.

Specifically, Dr. Swisher will examine:

• the need to monitor the real-world impact of AI-based decision-making tools proactively and continuously.
• approaches that result in improved technology reliability and better patient outcomes.

With her Project Rōnin team, Dr. Swisher has delivered AI-based systems that support clinical decision-making and natural language processing innovations. She also holds over 20 patents on machine learning and AI.

The Data Science Seminar Series presents talks from innovators in the cancer research and informatics communities both within and outside of NCI.

Speaker:

Christine Swisher, Ph.D.

Dr. Swisher leads teams of data scientists, statisticians, clinical informaticists, and machine learning experts to build technologies that solve challenging clinical problems. She is passionate about improving patient outcomes and delivering innovations safely and ethically.