Presenter: Eric Nyberg, PhD

This talk presents recent results on automatic question answering for biomedical and consumer health questions, drawn from CMU's participation in several recent open evaluations (including BioASQ, LiveQA, and MediQA). Despite promising achievements in recent evaluation campaigns, significant challenges must be solved before QA can be practically useful for experts and consumers.

Presenter: Haohan Wang, MS

The talk will start with the introduction of the most basic building blocks of deep learning models (especially convolutional neural networks) to build some statistical intuition of what deep learning is supposed to be capable of, and will show some evidence supporting that what is behind the promised human-level understanding of data is partially the model's tendency to capture the high-frequent superficial signals.

Presenter: Danielle Brown and Victoria Khersonsky
Presenter: Greg Cooper, MD, PhD

This talk describes an instance-specific causal Bayesian network (CBN) learning method that searches the space of CBNs to build a causal model that is specific to an instance (e.g., a patient). The search is guided by attributes of the given instance (e.g., patient symptoms, signs, lab results, and genotype). We describe the results of applying the method to molecular cancer data to estimate the gene alterations (e.g., gene mutations) that are driving the cancerous behavior of individual tumors, which are the instances in this application.

Presenter: Qi Yan, PhD

Asthma is a major cause of healthcare costs in children, particularly in the high-risk subgroup, Puerto Ricans. We aim to identify susceptibility genes for asthma in Puerto Ricans. We conducted GWAS and EWAS of asthma. We also conducted mQTL, eQTL and eQTM analyses to test for association between the top SNPs and DNA methylation and gene expression in nasal epithelium. We identified multiple SNPs, CpG sites and expressed genes associated with asthma.

Presenter: Deepika Mohan, MD, MPH

I plan to make the argument that we should use behavioral science principles when building quality improvement tools for physicians. I will discuss my research on the problem of trauma triage (an archetypal time-sensitive problem that occurs under conditions of uncertainty), with a brief digression to provide a primer on behavioral science, and sharing our efforts to use theoretically-based video games to recalibrate physician heuristics (intuitive judgments) in trauma.

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Presenter: No Colloquium
Presenter: Hatice Osmanbeyoglu, PhD

The process of matching pathway-targeted drugs to tumor mutational profile regardless of cancer type is critical in the development of targeted therapies. However, actionable mutations interact with distinct gene regulatory programs and signaling networks and can occur against different tumor-specific genetic backgrounds.