Posts – Page 6 – Duke AI Health

Maciej Mazurowski Joins Duke AI Health to Coordinate New Medical Imaging Initiative

Duke AI Health welcomes Maciej Mazurowski, PhD, who will join its Faculty Council as Director of Radiology Imaging. At AI Health, Dr. Mazurowski will coordinate the AI Health Initiative for Medical Imaging. This new effort will engage experts in machine learning and clinical medicine from across Duke’s campus to foster and accelerate the development, validation, and clinical implementation of machine learning algorithms for medical imaging. “I’m excited to undertake this new challenge and I’m looking forward to working with experts and leadership across the entire campus to build on existing technical and clinical strengths in medical imaging AI at Duke,” Dr. Mazurowski said.

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2022 Spring AI Health Proposal Studios

The mission of Duke AI Health is to enable the discovery, development, and implementation of artificial intelligence (AI) at Duke and beyond. A key component to achieving this goal is to foster high-impact, rigorous, and competitive proposals for scientific awards. The 2022 AI Health Proposal Studios will provide a structured opportunity for investigators to engage with Duke’s top data science expertise and thought leadership, and to receive review and feedback of the scientific components of their proposals. After seeing a strong response to the Proposal Studio concept and the following virtual learning experiences in 2021, AI Health plans to continue building on last year’s success with the overarching goal of fostering high-impact, rigorous, and competitive proposals for scientific awards.

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Closeup black and white photograph of an open laptop with hands poised to strike the keys. Image credit: Sergey Zolkin/Unsplash

Duke Health Data Analytics Community Praised for Commitment to Data Democracy

In a recent post at the Tableau blog, the data visualization company praises the Duke Analytics Community (DAC) for the group’s commitment to “taking data democracy to (the) next level.” The post, which is available at the Tableau website, singled out the Duke Cancer Institute’s Claire Howell and Duke University’s Rebecca McDaniel for recognition based on their initiative in helping to create a “department-agnostic space” where users of analytics software across the School of Medicine and Health System could share ideas and improve data access.

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Duke School of Nursing’s Michael Cary Selected as Inaugural AI Health Equity Scholar

Duke AI Health welcomes its first AI Health Equity Scholar, Michael P. Cary, PhD, RN, who is now beginning a yearlong scholarship supported by Duke AI Health and the Duke Clinical & Translational Science Institute. The AI Health Equity Scholars Program, which provides funding for Duke University faculty, staff, and postdoctoral scholars to actively collaborate with AI Health leadership, is focused on broadening Duke’s commitment to ethical and equitable data science and artificial intelligence (AI) in health applications.

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Announcing the Spring 2022 AI Health Data Studio Seminars

Duke AI Health is pleased to launch the AI Health Data Studio Seminar series this spring. This multi-part educational offering is designed for campus-based researchers at Duke who are interested in working with medical data but are unsure where to begin. Hosted by Senior Informacist Ursula Rogers, Chief AI Health Scientist Ricardo Henao, PhD, and Associate Director of Informatics Shelley Rusincovitch, MMCi, the series will feature data experts from across the Duke enterprise.Campus-based researchers are especially invited to attend along with anyone interested from the Duke community, including faculty, staff, and students.

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Blog: When Data Science Meets the Real World

Ursula Rogers shares a deeply personal perspective on medical data. “No patient or family should ever have to worry about whether bad data might be steering medical care in the wrong direction, or whether good data is failing to reach a care provider who can act on it.”

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Call for Applications: The AI Health Equity Scholars Program

Duke AI Health and the Duke Clinical & Translational Science Institute are pleased to announce a call for applications with the AI Health Equity Scholars Program. This program will support a minimum 1-year appointment for a faculty member, staff member, or postdoctoral scholar at Duke University. The AI Health Equity Scholars Program is a new initiative intended to broaden our commitment to ethical and equitable data science and artificial health (AI) applications, with direction from CTSI Director L. Ebony Boulware, MD, MHS, and AI Health Director Michael J. Pencina, PhD. The intention of this program is to broaden our expertise in considering and applying ethical and equitable principles for key initiatives within Duke AI Health. Applications must be submitted by Friday, December 10, 2021 by 10 PM (Eastern Time).

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Portrait of Duke AI Health Director Michael Pencina, PhD

Vice Dean for Data Science Michael Pencina, PhD, takes the role of Director for Duke AI Health

Given the rapid growth in and importance of harnessing health data as a tool, Mary Klotman, MD, Dean, Duke University School of Medicine, recently announced the key leadership appointment of Michael Pencina, PhD, Vice Dean for Data Science for the School of Medicine, as the Director of Duke AI Health effective October 13, 2021. Designed as a multidisciplinary initiative, AI Health intends to unlock the enormous opportunity to spur collaborations that will leverage knowledge and expertise from across campus.

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Call for Applications: Clinical Research with Electronic Health Records Data (CR-EHR) Course

Duke AI Health and the Duke Clinical & Translational Sciences Institute are pleased to announce a call for applications to the Spring 2022 Clinical Research with Electronic Health Records Data (CR-EHR) Course, with a November 19, 2021 application submission deadline. CR-EHR is an interdisciplinary course designed to engage both clinical and quantitative researchers in learning how to access and work with Duke EHR data. Data captured in the Duke EHR represent the broad spectrum of patient care delivered by Duke Health, which can be leveraged for a variety of research questions and study designs. Clinical trainees will develop a deeper understanding of the types of analytic studies that can be conducted with EHR data, while quantitative trainees will develop a deeper knowledge base for how to query and process EHR data.

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BLOG: Using Medical Records to Prepare Doctors and Patients for Difficult Conversations

Now more than ever, clinicians can access an incredible amount of data about their patients. Electronic health records (EHRs) offer a massive repository of information about each individual: notes of all kinds, laboratory results, imaging data, scanned forms, and saved images. Soon, we may even be able to add data from wearable devices such as personal fitness trackers into the mix. However, this breadth of information can be both a blessing and a curse. Clinicians can learn more about their patients from the medical chart than was previously possible—but only if they are able to rapidly and accurately sort through that information and find the most relevant points for a given clinical encounter.

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