The Mark Foundation for Cancer Research and Carnegie Mellon University co-organized a workshop on the intersection of artificial intelligence and cancer research that took place at the CMU Pittsburgh campus from April 24-26.
During the workshop, we explored how revolutions in machine learning and AI are enabling new and innovative analytical models for cancer research that can help address significant unmet medical needs. Investigators from around the US and abroad examined paths that can lead to the greatest impact for cancer patients in the clinic and beyond. Topics covered included predictive models for disease onset, progression, and response to treatment, as well as advanced image analytics, digital biomarkers, and molecular signature trajectories. Attendees came from many different areas of research including machine learning, computational biology, digital pathology, biomedical engineering, systems biology, and clinical oncology.
Programming for the workshop was designed to ignite collaborations among the attendees and stimulate ideas for new approaches that will lead to improved outcomes for cancer patients. A keynote address was provided by Dr. Stephen Friend, followed by an expert panel, focused breakout sessions, and short presentations by all. Participants worked together to identify opportunities in this important area of research. Emphasis was placed on identifying impactful questions as well as talking through some of the challenges, such as acceptance and uptake of new techniques by clinicians and patients, and access to data.
After the workshop, attendees were invited to submit collaborative AI/cancer research proposals as part of a special cycle of The Mark Foundation ASPIRE awards.
We look forward to continuing these engaging partnerships and collaborations with the scientific community in this exciting area of research, and hope these efforts will ultimately be fruitful in improving outcomes for cancer patients.