Presenter: Young Ji Lee, PhD, MS, RN

Patient engagement in their own care is essential to improve health outcomes and reduce cost. However, patient-engagement cannot be a one-sided issue. To be engaged fully, patients need to be well-informed, and supported by right healthcare providers who meet their needs and preferences. This presentation will discuss projects on enhancing patient engagement in self-management through informatics approach.

Presenter: Yang Liu, PhD

Early cancer detection currently relies on screening the entire at-risk population, as with colonoscopy and mammography. Frequent, invasive surveillance of patients at risk for developing cancer carries financial, physical, and emotional burdens because clinicians lack tools to accurately predict which patients will actually progress into malignancy.

Presenter: Xinghua Lu, MD, PhD

Cancer is a disease resulting from genome alterations.   Contemporary biotechnologies make genome-scale data from individual patients readily available, and personalized precision medicine based on specific genomic alterations of individual tumors presents promises of more effective therapy.   However, there are 3 major gaps hinder the translation from genome data  to personalized precision therapy.

Presenter: Victoria Khersonsky
Presenter: Jon Young and Amie Draper
Using Laboratory Data for Prediction of 30-Day Hospital Readmission
Amie Draper, BS, Doctoral Fellow
Presenter: JoAnna Hillman, Adam Handen and Adam Roth


JoAnna Hillman, MPH, Doctoral Fellow

Title: Improving Situational Awareness in a High-Burden Labor and Delivery Suite in Malawi

Presenter: Constantin Aliferis, MD, PhD, FACMI

Abstract:  This talk will address how advances in Machine Learning, especially used within a “Big Data” paradigm and exploiting new data generation and capture capabilities, are positioned to catalyze radical advances of Medical Science and the transformation of Healthcare.