University of Pittsburgh

Slides:

Advertisements

Similar presentations

Roland Grad & Pierre Pluye INFORMATION ASSESSMENT METHOD: A NEW KT TOOL.

Advertisements

Patient-/Family Centered Medical Home for Children Why hasn’t it spread further? Chuck Norlin, MD Professor of Pediatrics, University of Utah Adjunct Professor.

Clinical research and the electronic medical record: Interdisciplinary research agendas Michael G. Kahn MD, PhD Biomedical Informatics Core Director Colorado.

CHOICE Pathology Informatics 2010 Boston, Massachusetts DataReady ® : A Deployable Data Management and Integration System for Large-scale Cancer Repositories.

Prof. Carolina Ruiz Computer Science Department Bioinformatics and Computational Biology Program WPI WELCOME TO BCB4003/CS4803 BCB503/CS583 BIOLOGICAL.

Maria A. Wamsley, MD Professor of Clinical Medicine UCSF School of Medicine.

Contextual Inquiry of Enteric Disease Outbreak Investigation Processes to Improve Visualization Capacity for Public Health Surveillance Jonathan Anderson,

Initial Implementation of an Intelligent Patient Data Review Assistant (IPDRA) LTC Trinka Coster, MD Matthew Medlock, MD LTC Joseph Parker, MD Jim Ong,

Vision of how informatics enables a transformed health system Joyce Sensmeier MS, RN-BC, CPHIMS, FHIMSS, FAAN Vice President, Informatics, HIMSS President,

Clinical Registries Needs and Solutions Dr. Peter Greene, CMIO Diana Gumas, IT Director 1.

Leveraging the Electronic Health Record for Clinical Research John P. Glaser, PhD Vice President and CIO Partners HealthCare July 21, 2008.

Datamining MEDLINE for Topics and Trends in Dental and Craniofacial Research William C. Bartling, D.D.S. NIDCR/NLM Fellow in Dental Informatics Center.

Continual Development of a Personalized Decision Support System Dina Demner-Fushman Charlotte Seckman Cheryl Fisher George Thoma.

Bioinformatics and medicine: Are we meeting the challenge?

BlueMedics Evidence-based Patient Empowerment. Challenges Integration of clinical data –Horizontal - Sources –Vertical – Data Dynamic incorporation of.

Nursing Research Capacity Building. Background CON –opened as 9 th College at SQU in 2008 The CON’s next challenge is promoting nursing care based on.

Treatment Summary University of California San Francisco Center of Excellence for Breast Cancer Care PI: Laura J Esserman MD MBA; Edward Mahoney; Elly.

Using EPR2020 for Clinical Research Diana Gumas, Director of Clinical and Clinical Research IT 1.

Component 6 - Health Management Information Systems Unit 1-2 What is Health Informatics?

Center for Causal Discovery (CCD) of Biomedical Knowledge from Big Data University of Pittsburgh Carnegie Mellon University Pittsburgh Supercomputing Center.

Breast Cancer Surveillance Consortium: Progress in Understanding Screening Delivery and Early Detection Rachel Ballard-Barbash, MD, MPH, Associate Director,

Center for Predictive Computational Phenotyping (CPCP): Training Plans May 15, 2015 Debora Treu and Whitney Sweeney Center for Predictive Computational.

1 Health Informatics Research in CSCW: Why an Interdisciplinary Focus is Important Madhu Reddy PhD College of Information Sciences and Technology Center.

User Requirements and Engagement in Health Informatics Alistair Sutcliffe Sarah Thew, Oscar De Bruijn, Manchester Business School, Jock McNaught National.

Big Mechanism for Processing EEG Clinical Information on Big Data Aim 1: Automatically Recognize and Time-Align Events in EEG Signals Aim 2: Automatically.

Automatic Discovery and Processing of EEG Cohorts from Clinical Records Mission: Enable comparative research by automatically uncovering clinical knowledge.

Why Write A Grant? Elaine M. Hylek, MD, MPH Professor of Medicine Associate Director, Education and Training Division BU CTSI Section of General Internal.

Chapter 1: Section 1 What is Science?. What Science IS and IS NOT.. The goal of Science is to investigate and understand the natural world, to explain.

Research Tools Brought to you by the Clinical and Translational Science Institute Presented by: Terri Shkuda Systems Analyst Research Informatics The Penn.

N VISUAL ANALYTICS FOR HEALTHCARE: BIG DATA, BIG DECISIONS David Gotz Healthcare Analytics Research Group IBM T.J. Watson Research Center.

The Neural Engineering Data Consortium Mission: To focus the research community on a progression of research questions and to generate massive data sets.

Expediting Precision Medicine Initiatives for Clinical Genomics and Pharma through the Use of Knowledge Automation and Analytics Presenters: Dr. Scott.

TDM in the Life Sciences Application to Drug Repositioning *

Collaboration of IUCRCs to Solve Grand Challenges

OUHSC Vision/Initiatives for

Translational Research Why should you care about translational research? The public cares. Translation into therapies justifies spending on science.

Biomedical Data Science for Precision Medicine

Biomedical Data Science for Precision Medicine

Template for a 48”x36” poster

Emergency department pediatric psychiatric services

Scientific Reproducibility using the Provenance for Healthcare and Clinical Research Framework Satya S. Sahoo Collaborators/Co-Authors: Joshua Valdez,

Translational Informatics Applied to Drug Safety (TrIADS)

Shyam Visweswaran, MD, PhD

Areas of Research Xia Jiang Associate Professor of

KnowEnG: A SCALABLE KNOWLEDGE ENGINE FOR LARGE SCALE GENOMIC DATA

Discovery and Dissemination

Gregory Cooper Professor of Biomedical Informatics Director, Center for Causal Discovery Vice Chair Research, Department of Biomedical Informatics.

Development of Harvard Catalyst Imaging Consultation Service

Physicians, Patients, and the Electronic Health Record: An Ethnographic Analysis William Ventres, MD, MA.

Prescription Decision Support For Primary Care

Dr Gayan Perera Epidemiologist

Collaborating with the National Center for Biomedical Ontology

Project-Based Learning (PBL)

Harry Hochheiser Assistant Professor

Shyam Visweswaran, MD, PhD

Translational Informatics Applied to Drug Safety (TrIADS)

Discovery and Dissemination

Rebecca Crowley Jacobson, MD, MS

Areas of Research Xia Jiang Assistant Professor

Gregory Cooper Professor of Biomedical Informatics Director, Center for Causal Discovery Vice Chair, Department of Biomedical Informatics Research involves.

Biomedical Data Science for Precision Medicine

What is “Biomedical Informatics”?

Genes to Function to Therapeutics

What is CICATS? The University of Connecticut, in partnership with regional hospitals, state agencies, and community health care organizations, has.

Gregory Cooper Professor of Biomedical Informatics Director, Center for Causal Discovery Vice Chair Research, Department of Biomedical Informatics.

University of Pittsburgh

Shyam Visweswaran, MD, PhD

April 18th 2018 Moderator: Matthew Rioth

Shandong Wu, PhD Assistant Professor

From Innovation to Commercialization Access to Data

Presentation transcript:

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

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

NLPReViz: an interactive tool for natural language processing on clinical text Trivedi, et al. JAMIA 2017 doi: 10.1093/jamia/ocx070, nlpreviz.github.io NLPReViz - NLP with expert-driven review and revision

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

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 2016 https://doi.org/10.1186/s12911-016-0358-4 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. 2015 AMIA Annual Symposium; 2015 Nov 14-18; San Francisco, California p.1967-1975. 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

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

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 LM011838-01, 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)