Health Informatics Invited Speaker Series

The Invited Speaker Series is an extension of our Health Informatics Grand Rounds. In this series, top informaticians from around the country will share their current research with the University of Minnesota informatics community. This series is open to the public.

The series will generally be on Thursdays from 3:30-4:30, but dates and times may vary.

September 11, 2019 The OptumLabs Research Collaborative: A unique academic/industry partnership

September 11, 2019 The OptumLabs Research Collaborative: A unique academic/industry partnership

     

Thomas R. Clancy, MBA, PhD, RN, FAAN
Clinical Professor, Ad Honorem
University of Minnesota School of Nursing
Minneapolis, MN

Lisiane Pruinelli, PhD, RN
Assistant Professor
University of Minnesota School of Nursing
Minneapolis, MN

Jean F. Wyman, PhD, RN, APRN, GNP-BC, FAAN, FGSA
Professor and Cora Meidl Siehl Chair in Nursing Research
University of Minnesota School of Nursing
Minneapolis, MN

 

September 11, 2019
2:15 p.m. - 3:15 p.m.
Link to Live Stream

Description:
The OptumLabs Research Collaborative is a unique intra-professional, academic/industry partnership that provides researchers access to linked health insurance, electronic health record and consumer behavior data for over 200 million patient records.  The University of Minnesota is one of the original members of the Research Collaborative which now includes 27 academic and professional organizations. Multiple University of Minnesota faculty have utilized the OptumLabs Data Warehouse (OLDV) for funded studies. The University of Minnesota School of Nursing acts as the support center for any University of Minnesota faculty member who desires to access the database for research purposes.  This presentation will provide an overview of the Research Collaborative, current studies and demonstrate how faculty with or without an informatics background can use the OLDV to conduct research in large complex databases.

 

 

 

May 16, 2019-Data Science and Informatics for Panomic Microbiome Discoveries

May 16, 2019-Data Science and Informatics for Panomic Microbiome Discoveries

Alexander Alekseyenko, PhDAlexander V. Alekseyenko
Program for Human Microbiome Research
Biomedical Informatics Center
Medical University of South Carolina

Thursday, May 16
3:30 p.m. - 4:30 p.m.
2-690 Moos Tower

Live stream

Microbiome is a term used to describe the collection of all microorganisms that colonize our bodies. Whereas understanding the human genome has received enormous amount of attention in the last 20 years, the impact of host associated microbiome genomes (the metagenome) and their function in human health and disease is still in very early stages of being conceptualized. The recent surge in microbiome science has been afforded by increasing availability of technologies, such as high-throughput DNA sequencing, mass spectrometry, automated cell sorting, etc. Most notably, of course, the ability to sequence hundreds of individual microbiomes in a single run of a sequencing instrument has resulted in a perfect storm of microbial community profiling datasets addressing a vast array of biomedical questions. This presentation will motivate the need for microbiome specific data analytic techniques. I will highlight a few promising analytic approaches and elements of a general framework for integrating high dimensional host-microbiome data. I will also describe how informatics can accelerate microbiome research by simplifying research access to human microbiome specimens from clinically relevant patient populations via a Living µBiome Bank.

April 4, 2019-AI for healthcare - bridging the gap between human intelligence and machine intelligence

April 4, 2019-AI for healthcare - bridging the gap between human intelligence and machine intelligence

Picture of Hongfang LiuHongfang Liu, Ph.D
Professor of Biomedical Informatics, Mayo College of Medicine 
Chair, Division of Digital Health Sciences
Director, Biomedical Informatics, Mayo Clinic Center of Clinical and Translational Science
Director, Clinical Natural Language Processing Program

Thursday, April 4
2:30 p.m. - 3:30 p.m.
2-470 Phillips Wangensteen Building
Recording

On average, a patient generates 80 megabytes of imaging and EHR data each year.  For a healthcare organization, this trove of data from patients has an obvious clinical, financial, and operational value. However, the value of big data in health care is only realized when this raw information is converted into knowledge that changes the practice. The next generation of healthcare delivery requires a team effort from data science, delivery science, and implementation science to ensure that the right patient receives the right care from the right provider at the right time and the right place. In this talk, I will discuss opportunities and challenges faced when bringing AI for healthcare illustrated through some of our ongoing efforts.

March 5, 2019-Biomedical Informatics and Precision Medicine are Laying the Framework for the Next Generation of Discovery

March 5, 2019-Biomedical Informatics and Precision Medicine are Laying the Framework for the Next Generation of Discovery

Picture of Sean MooneySean Mooney, PhD
Professor, Department of Biomedical Informatics and Medical Education
Chief Research Information Officer, UW Medicine
University of Washington

Tuesday, March 5
12:00 p.m. - 1:00 p.m.
2-650 Moos Tower
Link to Live Stream

It is an opportune time to be engaged in the research and application of informatics in biomedicine.  The increased use of electronic and personal health records and personal mobile devices is creating many opportunities at research academic medical centers.  At the University of Washington, we are laying the ground work to build the informatics and information technology infrastructure to support research on personalized approaches, and we are beginning to see the early successes of these efforts. There are many challenges, for example, whole exome and whole genome sequencing is continuing to challenge researchers with a wealth of genetic variants of unknown disease effects.  The genetic causes of penetrance and phenotypic expressivity often have no known molecular basis. In this presentation, I will discuss our support of data for research use within UW Medicine, our efforts to build new machine learning and data science approaches using clinical datasets, and our efforts to develop new methods to interpret human genome sequences.  Further, we are leveraging the crowd by organizing and participating in community challenges (critical assessments) to build a better understanding of the types of approaches that perform well in genome interpretation and in what context.  I will describe the newly founded Center for Data To Health (CD2H) and how we are facilitating informatics throughout the CTSA program nationally and how CTSA hubs can further engage the CD2H center. 

November 26, 2018- The Role of Informatics in the Implementation of Population Precision Health

November 26, 2018- The Role of Informatics in the Implementation of Population Precision Health

Marc Williams, MDMarc Williams, MD 
Director, Genomic Medicine Institute

November 26
3:30 p.m. - 4:30 p.m.
2-470 Phillips Wangensteen Building
Recording

This talk will provide a brief overview of the terminology and philosophy of the emerging field of precision health followed by a presentation of the Geisinger Precision Health project, the MyCode Community Health Initiative. The focus will be on the information systems and informatic approaches needed to support a precision health program emphasizing the gaps and opportunities for implementation research.

 

 

October 23, 2018-The FASK Algorithm for Cyclic Models, with Applications

October 23, 2018-The FASK Algorithm for Cyclic Models, with Applications

Joseph Ramsey, PhDJoseph Ramsey, Ph.D.
Special Faculty and 
Director of Research Computing
Department of Philosophy Carnegie Mellon University

 

 

October 23
3:30 p.m. - 4:30 p.m.
2-470 Phillips Wagensteen Building
Recording

Synopsis: In this talk, a novel algorithm, FASK ("Fast Adjacency Skewness"), will be discussed, which addresses problems with skewed variables where there may be cycles arbitrarily situated throughout the model. The cycles may either be tight, involving only two variables, or longer cycles involving many variables. Some theory for the algorithms will be discussed, followed by applications to three different domains: (a) fMRI causal modeling, (b) single-cell cytology causal modeling, and (c) simulated diffusion and advection in climate models.

Bio: Dr. Ramsey earned his Ph.D. in Philosophy at the University of California at San Diego, with an emphasis on Cognitive Science. He has worked on many grant-funded projects, beginning with work for NASA Ames on detecting carbonates in rocks using mineral spectra, using a causal algorithm, then on software for natural deduction, and several projects applying causal research to practical scientific problems in various domains, including cell biology, wildfire analysis, and causal analysis of fMRI time series, to give a few. Since 1998 he has been the lead developer on the TETRAD projects, an open source project for causal analysis, where he has designed and implemented many causal search algorithms, several of which have come to be used in the scientific community. He is currently on the Philosophy faculty at Carnegie Mellon University as Director of Research Computing, where he's been since 1998.

 

 

Translational Informatics in Cancer Precision Medicine: Insights from hematologic malignancies and autoimmune disorders

Translational Informatics in Cancer Precision Medicine: Insights from hematologic malignancies and autoimmune disorders

Picture of Matthew BreitensteinMatthew Breitenstein, Ph.D.
Instructor of Informatics Department of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, Senior Fellow – Institute for Biomedical Informatics (IBI), Senior Fellow – Center for Pharmacoepidemiology, Research & Training (CPeRT), University of Pennsylvania, Philadelphia, PA

 

September 18
3:30 p.m. - 4:30 p.m
2-580 Moos Tower
Recording

This talk will highlight translational informatics approaches for advancing precision medicine knowledge within the cancer control setting. Particularly, where insights obtained from multi-omic comparisons and reverse translation serve as a pivot for treatment personalization or advancing mechanistic/etiologic insights of disease. Scientifically, this talk will be focused within diffuse large B-cell lymphoma and systemic lupus erythematosus, a B-cell malignancy and autoimmune disorder, respectively, and overlapping targeted therapies. A novel pharmacogenomic determinant of response to rituximab identified using translational informatics approaches will be discussed in depth.