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University of Pittsburgh

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Presentation on theme: "University of Pittsburgh"— Presentation transcript:

1 University of Pittsburgh
Department of Biomedical Informatics Biomedical Knowledge Navigation: Interactive tools for clinical and research insight Harry Hochheiser, PhD Assistant Professor Department of Biomedical Informatics Assistant Professor Intelligent Systems Program Director Biomedical Informatics Training Program Center for Causal Discovery ( University of Pittsburgh Hello everyone. Thank you for coming. Today I will be talking about Buck Cash

2 The data interpretation challenge
Clinicians and translational researchers are swamped with data Lab measurements, meds, clinical notes, imaging data in EMRs Genomics, microbiome, expression profiles, phenotypes.. Experts need tools that Get them closer to the data Facilitate exploration and hypothesis generation Enable clear and semantically-well-founded descriptions of data Support knowledge work as an ongoing process Approach Qualitative investigation of problem domains,user needs, and workflows Iterative prototyping and refining of ideas Mixed-methods (qualitative and quantitative) evaluations

3 NLPReViz: an interactive tool for natural language processing on clinical text
Trivedi, et al. JAMIA 2017 doi: /jamia/ocx070, nlpreviz.github.io NLPReViz - NLP with expert-driven review and revision

4 GRADS: Genomic Research In Alpha-1 Antitrypsin Deficiency Syndrome and Sarcoidosis
Data portal for observational clinical sample Goal : Enable interactive cohort selection for dataset of clinical, genome, microbiome, and virome data

5 Clinical & Clinical Research Informatics
DeepPhe: Deep phenotyping of longitudinal cancer data extracted via NLP Goal : Develop multi-level data models for cancer progression and visual tools for cohort identification for retrospective studies Hochheiser, H, Castine M, Harris D, Savova G, Jacobson RS An Information Model for Cancer Phenotypes BMC Medical Informatics and Decision Making Learning EMR: Use predictive models to identify and highlight items of interest to clinicians reviewing cases with EMRS, thus reducing cognitive load Goal : Explore and evaluate interface designs that will emphasize material predicted to be relevant without causing disorientation or blindness to relevant material King A, Cooper GF, Hochheiser H, Clermont G, Visweswaran S. Development and Preliminary Evaluation of a Prototype of a Learning Electronic Medical Record System AMIA Annual Symposium; 2015 Nov 14-18; San Francisco, California p Best Student Paper King A, Hochheiser H, Visweswaran S, Clermont C, Cooper GF Eye-tracking for clinical decision support: A method to capture automatically what physicians are viewing in the EMR 2017 AMIA Joint Summits Best Student Paper, Clinical Research Informatics

6 Other Current Projects
Center for Causal Discovery: Advancing the application of causal discovery to biomedicine Goal : Tools and metadata support for reproducible causal analyses Addressing gaps in clinically useful evidence on drug-drug interactions: Developing improved tools for interpreting potential drug-drug interaction information Goal : Conduct inquiry into expert needs and workflows; design search engine over curated PDDI data. Quantifying Electronic Medical Record Usability to Improve Clinical Workflow: Using in-situ recording of clinician interactions with EMR during patient visits to understand factors influencing usability and perceived workflow Goal : Use understanding of EMR use in clinic to guide improved designs

7 Grant Funding/Collaborations
GRADS: 1U01HL112707, N. Kaminski (Yale, PI), S. Wiesnewski (Pitt), M. Becich (Pitt), A. Morris (Pitt), B. Methe (Pittt), E. Ghedin (NYU) DeepPhe: 1 U24 CA184407, R. Jacobson (Pitt, co-PI), G. Savova (Boston Children’s Hospital, co-PI) Learning EMR: 1 R01 LM012095, S. Visweswaran (Pitt, PI), G. Cooper (Pitt), G. Clermont (Pitt), M. Hauskrecht (Pitt) Center for Causal Discovery: U54HG008540, G. Cooper (Pitt, co-PI), I. Bahar (Pitt, co-PI), C. Glymour (CMU), R. Scheines (CMU), many others… Addressing gaps in clinically useful evidence on drug-drug interactions: 1 R01 LM , R. Boyce (PI, Pitt) Quantifying Electronic Medical Record Usability to Improve Clinical Workflow: 5R01HS021290, Z. Agha (West Health Foundation & UCSD, PI), C. Weir (Utah), N. Weibel (UCSD), Y. Chen (UC Irvine). R Street (Texas A&M) Other Collaborators: W. Chapman (Utah), R. Hwa (Pitt), J. Wiebe (Pitt), P. Empey (Pitt)

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