Posts – Page 3 – Duke AI Health

New video highlights success of the spring 2023 poster showcase

A new video highlights the experience of the Duke Health Data Science Poster Showcase, held April 24, 2023 at the Mary Duke Biddle Trent Semans Center for Medical Education.

Created by Duke videographer Michael Blair with support from the Duke Center for Computational Thinking, the video features interviews by Matt Engelhard, PhD, an Assistant Professor of Biostatistics and Bioinformatics and faculty director of the AI Health Data Science Fellowship Program; and Hanxue Gu, a PhD student in the Electrical and Computer Engineering department and a member of the Mazurowski Lab who won the award for Best Computational Thinking Poster.

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Composite image featuring photos of 32 speakers

AI Health Spring 2023 Learning Experiences

By Tiffany Torres

The Spring 2023 semester was comprised of 15 AI Health seminars that attracted 866 attendances, including people who attended multiple sessions.

The AI Health seminar series builds upon the success of our previous “Plus Data Science” learning experiences from 2017 – 2021 under the leadership of Larry Carin, which convened 59 in-person learning experiences and 66 virtual learning experiences.

Since its launch in 2018, +DS has held a cumulative 140 learning experience sessions (both in-person and virtual).

The Spring 2023 semester featured 32 data experts from across multiple areas of interest.

Duke Departments and Schools Represented:

Biostatistics and Bioinformatics
Duke Health Technology Solutions
Biomedical Imaging
Family Medicine and Community Health
School of Nursing
Civil and Environmental Engineering
Electrical and Computer Engineering
Computer Science
CTSI
Radiology
Pediatrics
Neurosurgery
Biomedical Engineering
Population Health Sciences
Geriatrics
Office of Evaluation and Applied Research Partnership

We are looking forward to the Fall 2023 learning experiences, which will begin in September. A list of upcoming events can be found at https://aihealth.duke.edu/events/

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Duke Researchers Develop Prediction Model to Identify Children With Complex Health Needs At Risk for Hospitalization

An important study led by Duke’s David Ming, MD, and AI Health’s Benjamin Goldstein, PhD, and Nicoleta Economou, PhD, on the use of predictive modeling to identify children with complex health needs who are at high risk for hospitalization, was recently published in Hospital Pediatrics, the official journal of the American, Academy of Pediatrics. The study analyzed data from electronic health records and found that certain demographic, clinical, and health service use factors were associated with a higher risk of future hospitalization. The authors, including Duke’s Richard Chung, MD, and Ursula Rogers, BS, suggest that the use of predictive modeling can help identify children with complex health needs who may benefit from targeted interventions to prevent hospitalizations and improve outcomes. The study is accompanied by a commentary by University of Wisconsin Neil Munjal, MD, MS, titled ‘Machine Learning: Predicting Future Clinical Deterioration in Hospitalized Pediatric Patients,’ which describes the Duke researchers’ machine learning approach as “thought-provoking.”

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Photograph showing approximately 60 people in a group

April Poster Showcase Features Duke’s Successes in Health Data Science

A poster showcase held on Monday, April 24, 2023 at the Mary Duke Biddle Trent Semans Center for Medical Education featured 28 posters in health data science. This cross-disciplinary event was hosted by multiple organizations, including Duke AI Health, the Laboratory for Transformative Administration, and the Center for Computational Thinking. Poster topics were centered around health data science and covered a wide range of topics including statistics, informatics, machine learning, data engineering, implementation, process engineering, technology development, and applications. The posters were submitted by people at all stages of their careers, including students, trainees, staff, and faculty. Information tables also shared programs and resources relevant to health data science at Duke.

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Join us for the Health Data Science Poster Showcase on April 24

The Health Data Science poster showcase will be held in person on Monday, April 24 from 12:00-2:00 PM. We’re excited that this cross-disciplinary event will be hosted by multiple organizations, including Duke AI Health, the Laboratory for Transformative Administration, and the Center for Computational Thinking.

The poster display will take place in the Mary Duke Biddle Trent Semans Center for Medical Education (Trent Semans) on the 6th floor and we’ll serve light refreshments.

More than 25 posters will be presented, including Duke participants from: AI Health Fellowship Program; Biomedical Engineering; Clinical and Translational Science Institute (CTSI); Computer Science; Department of Biostatistics and Bioinformatics; Department of Internal Medicine; Department of Neurosurgery; Department of Surgery; Division of Geriatrics, Department of Medicine; Division of Hematology, Department of Medicine; Duke Clinical Research Institute (DCRI); Electrical and Computer Engineering (ECE); Duke Health Technology Solutions (DHTS); Laboratory for Transformative Administrative (LTA); Master of Management in Clinical Informatics (MMCi); OB-GYN; and Trinity College of Arts & Sciences.

Information tables will include programs from across Duke: The + Programs for Students; Duke AI Health; Biostatistics, Epidemiology, and Research Design (BERD); Center for Computational Thinking; Duke Data Analytics Community; and the Master of Management in Clinical Informatics.

Poster awards will include Best Computational Thinking Poster and the Good DEEDS Award (Ethical and Equitable Data Science).

Please join us! All are welcome, and light refreshments will be served.

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Coalition for Health AI Unveils Blueprint for Trustworthy AI in Healthcare

The Coalition for Health AI (CHAI) released its highly anticipated “Blueprint for Trustworthy AI Implementation Guidance and Assurance for Healthcare” (Blueprint). The Blueprint addresses the quickly evolving landscape of health AI tools by outlining specific recommendations to increase trustworthiness within the healthcare community, ensure high-quality care, and meet healthcare needs. The 24-page guide reflects a unified effort among subject matter experts from leading academic medical centers and the healthcare, technology, and other industry sectors, who collaborated under the observation of several federal agencies over the past year.

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Duke Health Selected to Help Move Health Research Into Clinical Practice

Duke University Health System has been selected by the Patient-Centered Outcomes Research Institute (PCORI), an independent, nonprofit research organization, to participate in a new effort to close the gap between high-quality medical research and implementation of that evidence to improve patient outcomes.

The PCORI project will support ongoing efforts at Duke centered on work begun through the Duke Quality System. Led by Richard P. Shannon, M.D, Duke Health senior vice president and chief quality officer, the Duke Quality System aims to provide “perfect patient care,” a concept that not only includes providing timely, evidence-based patient care, but also ensuring that the care is done right the first time, without defects, waste, or inequity.

Shannon, who also serves as chief medical officer for Duke Health, most recently has led the development of the Duke Collaborative to Advance Health Equity (CACHE), a community-driven program that extends the quality system model by harnessing data science to find and eliminate racial disparities in health care.

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Flyer displaying the call for participation

Call for Participation: Posters for the April 24 Duke Health Data Science Showcase

The Health Data Science poster showcase will be held on Monday, April 24 from 12:00-2:00 PM in-person in the Mary Duke Biddle Trent Semans Center for Medical Education (Trent Semans). We’re excited that this cross-disciplinary event will be hosted by multiple organizations, including Duke AI Health, the Laboratory for Transformative Administration, and the Center for Computational Thinking.

We invite any member of the Duke community to propose a poster entry for participation in this event, including students, trainees, staff, and faculty. This experience is intended to be especially valuable to individuals seeking to gain experience in presenting their work in front of a scientific audience, and the poster itself can become a valuable part of an academic portfolio.

Submit your poster topic at: https://duke.qualtrics.com/jfe/form/SV_1HuvnGKOY4YMa9w

The preferred deadline for poster topics to be submitted is Monday, March 13, 2023 by 11:59 PM (Eastern time).

Update on March 10: We’ve heard from several people that their research is ongoing, and we’ve decided to accept poster topics on an rolling basis, to allow everyone the full opportunity to participate.

Poster topics must be centered around health data science, but can cover a wide range of potential topics, such as statistics, informatics, machine learning, data engineering, implementation, process engineering, technology development, or applications. We especially encourage submissions describing experiences with Duke data sources. Student posters describing class projects (at both the undergraduate and graduate levels) are also encouraged.

After you submit your topic, you’ll then receive a poster template with the correct dimensions.

You’ll need to submit your finalized poster by Friday, April 14 in order to have it printed. If your poster is accepted, the event organizers will print it for you and you will have no cost to participate. The showcase will include poster judging, with recognitions including best poster.

We’re excited to do another poster session after the very successful December event, and we invite you to join us! Please email aihealth@duke.edu if you have any questions.

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AI Health Seminar Series Success from 2022

The fall 2022 semester was comprised of 9 AI Health seminars that attracted 463 attendances, including people who attended multiple sessions. Across all of 2022, the AI Health seminar series has hosted 22 virtual seminars with 1,820 cumulative attendances. The AI Health seminar series builds upon the success of our previous “Plus Data Science” learning experiences from 2017 – 2021 under the leadership of Larry Carin, which convened 59 in-person learning experiences and 66 virtual learning experiences. Since its launch in 2018, +DS has held a cumulative 125 learning experience sessions (both in-person and virtual). – Metrics by Tiffany Torres

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Algorithms to Assess Stroke Risk are Markedly Worse for Black Americans

Current medical standards for accessing stroke risk perform worse for Black Americans than they do for white Americans, potentially creating a self-perpetuating driver of health inequities. A study, led by Duke Health researchers and appearing online Jan. 24 in the Journal of the American Medical Association, evaluated various existing algorithms and two methods of artificial intelligence assessment that are aimed at predicting a person’s risk of stroke within the next 10 years. The study found that all algorithms were worse at stratifying the risk for people who are Black than people who are white, regardless of the person’s gender. The implications are at the individual and population levels: people at high risk of stroke might not receive treatment, and those at low or no risk are unnecessarily treated.

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