PSB 2019 Text Mining and Machine Learning for Precision Medicine Workshop: program

Keynote speaker: Christopher Chute

Talk Title: Comparability and Consistency of NLP for Biomedical Discovery and Translation

Dr. Chute is the Bloomberg Distinguished Professor of Health Informatics, Professor of Medicine, Public Health, and Nursing at Johns Hopkins University, and Chief Research Information Officer for Johns Hopkins Medicine.
Dr. Chute’s career has focused on how we can represent clinical information to support analyses and inferencing, including comparative effectiveness analyses, decision support, best evidence discovery, and translational research. He has had a deep interest in semantic consistency, harmonized information models, and ontology. His current research focuses on translating basic science information to clinical practice, and how we classify dysfunctional phenotypes (disease).

Panelists

Graciela Gonzalez-Hernandez, Ph.D., is an Associate Professor of Informatics in the Department of Biostatistics and Epidemiology and Director of the Health Language Processing Lab at the Perelman School of Medicine, University of Pennsylvania

Hongfang Liu, Ph.D., is a professor of biomedical informatics in the Mayo Clinic College of Medicine, consultant in the Department of Health Sciences Research at Mayo Clinic, and leads Mayo Clinic’s clinical natural language processing

Zhiyong Lu, Ph.D., is the Deputy Director for Literature Search at the National Center for Biotechnology Information (NCBI)

Emek Demir, Ph.D., is an Associate Professor of Computational Biology, Molecular and Medical Genetics at the Oregon Health & Science University. His work focuses on large scale curation and assembly of molecular pathways.

Schedule

Date: Saturday, January 5, 2019

2:30 – 2:40 Opening Remarks

2:40 – 3:00 Keynote Talk by Dr. Christopher Chute

3:00 – 3:15 Development and Validation of the PEPPER Framework (Prenatal Exposure PubMed ParsER) with Applications to Food Additives
Mary Regina Boland, Aditya Kashyap, Jiadi Xiong, John Holmes and Scott Lorch

3:15 – 3:30 Mining HPV Vaccination Health Beliefs from Twitter Using Deep Learning: A Longitudinal Analysis of Four – Year Data (2014 – 2017)
Jingcheng Du, Yang Xiang, Jing Huang, Xinyuan Zhang, Rui Duan, Jiayi Tong, Jiang Bian, Sahiti Myneni, Yong Chen and Cui Tao

3:30 – 3:45 Data integration for prediction of time to insulin in type 2 diabetes patients
Rikke Linnemann Nielsen, Louise Donnelly, Agnes Martine Nielsen, Kaixin Zhou, Bjarne Ersboll, Ewan Pearson and Ramneek Gupta

3:45 – 4:00 Longitudinal visualization of heterogeneous data from neurodegenerative patients for clinical hypothesis generation
Sebastian Schaaf, Mischa Uebachs, Vyara Tonkova, Kilian Krockauer, Lisa Langnickel, Philipp Koppen and Juliane Fluck

4:00 – 4:15 MultiPLIER: a transfer learning framework reveals systemic features of rare autoimmune disease
Jaclyn Taroni, Peter Grayson, Qiwen Hu, Sean Eddy, Matthias Kretzler, Peter Merkel and Casey Greene

4:15 – 4:30 A statistical framework for data integration through graphical models with application to cancer genomics
Yuping Zhang, Zhengqing Ouyang and Hongyu Zhao

4:30 – 5:10 Panel

5:10 – 5:30 Plenary Discussion