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The rapid adoption of electronic health records (EHR) provides a comprehensive source for exploratory and predictive analytic to support clinical decision-making. In this paper, we investigate how to utilize EHR to tailor treatments to individual patients based on their likelihood to respond to a therapy. We construct a heterogeneous graph which includes(More)
Patient medical records today contain vast amount of information regarding patient conditions along with treatment and procedure records. Systematic healthcare resource utilization analysis leveraging such observational data can provide critical insights to guide resource planning and improve the quality of care delivery while reducing cost. Of particular(More)
Drug therapeutic indications and side-effects are both measurable patient phenotype changes in response to the treatment. Inferring potential drug therapeutic indications and identifying clinically interesting drug side-effects are both important and challenging tasks. Previous studies have utilized either chemical structures or protein targets to predict(More)
Risk stratification is instrumental to modern clinical decision support systems. Comprehensive risk stratification should be able to provide the clinicians with not only the accurate assessment of a patient's risk but also the clinical context to be acted upon. However, existing risk stratification techniques mainly focus on predicting the risk score for(More)
Drug-drug interaction (DDI) is an important topic for public health, and thus attracts attention from both academia and industry. Here we hypothesize that clinical side effects (SEs) provide a human phenotypic profile and can be translated into the development of computational models for predicting adverse DDIs. We propose an integrative label propagation(More)
Therapeutic indications and drug side-effects are both measureable human behavioral or physiological changes in response to the treatment. In modern drug development, both inferring potential therapeutic indications and identifying clinically important drug side-effects are challenging tasks. Previous studies have utilized either chemical structures or(More)
Disease risk prediction has been a central topic of medical informatics. Although various risk prediction models have been studied in the literature, the vast majority were designed to be single-task, i.e. they only consider one target disease at a time. This becomes a limitation when in practice we are dealing with two or more diseases that are related to(More)