Recent advances in medicine and electronic book-keeping have greatly increased the amount of medical data available for research and clinical decision making. Electronic Health Records include information about test results, lab reports, medical images, genomics, treatments, outcomes, and family histories. Together with recent advances in data mining and machine learning, it now seems possible to realize the grand vision of predictive personalized medicine.
Statistical Relational Learning (SRL) combines the powerful formalisms of probability theory and first-order logic to handle uncertainty in large, complex problems. In this talk, I illustrate the potential of SRL to achieve an important sub-goal of predictive medicine: early detection. Specifically, I will present SRL approaches for (1) identifying young adults who are at high risk of developing Coronary Heart Disease in middle and later life, and (2) identifying the set of patients who have or will have Alzheimer’s Disease by analyzing their brain MRI images. I will present a general approach for learning SRL models based on Functional-Gradient Boosting. I will adapt this algorithm for the above mentioned challenging tasks to produce state-of-the-art results in three real-world medical studies. I will outline other interesting problems in personalized medicine that we are addressing using SRL and conclude on the optimistic note that predictive personalized medicine is within reach in the near future.
Sriraam Natarajan is an Assistant Professor at the Wake Forest University School of Medicine. He was previously a 3 year Post-Doctoral Research Associate at University of Wisconsin-Madison and graduated with his PhD from Oregon State University. His research interests lie in the field of Artificial Intelligence, with emphasis on Machine Learning, Statistical Relational AI, Reinforcement Learning and Graphical Models with applications in Biomedicine and Health Informatics. He is a Senior Program Committee member of IJCAI 2013 and has served on the PC of several conferences/workshops such as AAAI, IJCAI, ICML, ECML, ILP and SRL. He has co-organized the AAAI 2010 and the UAI 2012 workshops on Statistical Relational AI (StarAI), the 2012 Workshop on SRL and the ECML PKDD 2011 and 2012 workshops on Collective Learning and Inference on Structured Data (Co-LISD). He is co-organizing the AAAI 2013 workshop on StarAI.