Registration open for FAIR HEALTH workshop on January 8, 2024

FAIR HEALTH (Fostering AI/ML Research for Health Equity and Learning Transformation)
Monday, January 8, 2024, 9:00 AM – 12:00 PM
In person at Sarah Duke Gardens in Kirby Horton Hall

This event is open to anyone who is passionate about advancing healthcare through innovation while ensuring health equity and fairness in clinical algorithms, including faculty, staff, and students.

This workshop will delve into the critical issue of algorithmic bias and clinical decision making. This is an opportunity to gain essential insights and practical strategies to identify, mitigate, and evaluate bias in clinical algorithms. We will also explore the legal and ethical implications of algorithmic bias in healthcare, an aspect that is gaining increasing importance in today’s dynamic healthcare landscape. To enrich the workshop and encourage active participation, we have incorporated a combination of lectures and an interactive case study discussion, making it an even more rewarding experience for all attendees. By engaging in this workshop, and learning from one another, we can pave the way for a future where healthcare algorithms enhance patient care, minimize bias, and prioritize equity.

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Vanderbilt and Duke Awarded Moore Foundation Grant to Improve Oversight of AI Technology in Health Care Systems

Vanderbilt University Medical Center (VUMC) and Duke University School of Medicine were awarded a $1.25 million grant from the Gordon and Betty Moore Foundation for the project “Measuring Artificial Intelligence (AI) Maturity in Healthcare Organizations.”  Working with the Coalition for Health AI (CHAI) and the University of Iowa, a team of experts will leverage the grant to develop a maturity model framework. The project leads are Peter Embí, MD, MS, and Laurie Novak, PhD, MHSA, from VUMC; and Michael Pencina, PhD, and Nicoleta Economou, PhD, from Duke. This framework will outline the essential capabilities that health systems must establish to ensure they are well-prepared for the trustworthy utilization of AI models.

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Duke AI Health welcomes Ozanan R. Meireles, MD

The Duke Department of Surgery is pleased to announce the appointment of Ozanan R. Meireles, MD, as the department’s first Vice Chair for Innovation, effective Jan. 2, 2024.

Dr. Meireles is an internationally known authority in surgical applications of Artificial Intelligence (AI) and comes to us from Massachusetts General Hospital (MGH) where he specializes in minimally invasive surgery and runs the MGH Surgical AI and Innovation Lab (SAIIL). This lab boasts an impressive and longstanding close collaboration of more than eight years with MIT’s renowned Computer Science and Artificial Intelligence Lab (MIT-CSAIL), a partnership cultivated under the guidance of Professor Daniela Rus. Subsequently, he is bringing SAIIL to Duke as director of the lab. He will work within the School of Medicine as Surgical Director of Duke AI Health and advise on surgical AI applications emerging in the Health System. He will also serve as Vice Chair of Innovation for the Department of Surgery.

“We are delighted to welcome Dr. Meireles to Duke, where the intersection of medicine and data science serves as the cornerstone for innovation in health research and healthcare delivery,” says Michael Pencina, PhD, Chief Data Scientist for Duke Health, and Director of Duke AI Health. “His expertise in AI will play a vital role in advancing our data-driven collaborative initiatives, and we look forward to the groundbreaking discoveries and advancements that will result from his contributions.”

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Flyer for the 2023 EHR-SDW

Registration now open for the Electronic Health Record (EHR) Study Design Workshop

Duke AI Health is pleased to announce the Duke Electronic Health Records Study Design Workshop (EHR-SDW) 2023. The workshop will be offered in December as a virtual five-day class (December 4 – 8, 2023) that provides foundational lectures and hands-on studios on the fundamentals of working with and designing EHR based studies.

The EHR-SDW is targeted toward individuals interested in learning about how to work with and conduct studies using electronic health records (EHR) data. EHR data are a widely available form of real-world data that have become standard in studies ranging from clinical trials, comparative effectiveness, risk prediction, and population health. The EHR-SDW will introduce the components of EHR data and introduce considerations for design of effective studies. In addition to didactic lectures, participants will get hands-on experience in working with publicly available tools to facilitate EHR studies (e.g., RxNorm, CCS codes, geocoding) as well as feedback on effective study designs that they will work on. The course will be conducted virtually via Zoom.

The deadline for registration is Tuesday, November 28, 2023.

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Flyer for the 2023 poster showcase call for participation

Call for Participation: Health Data Science Posters for December 8 Showcase

The next Duke Health Data Science poster showcase will be held on Friday, December 8, 2023 from 11:00 AM – 1:00 PM in person at the Sarah Duke Gardens Kirby Horton Hall.

We invite any member of the Duke community to submit a poster topic and participate in this event, including students, trainees, staff, and faculty.

Poster topics 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. Posters describing class projects are also encouraged.

The preferred deadline for poster topics to be submitted is Wednesday, November 15, 2023.

Read more about this call for participation at https://aihealth.duke.edu/2023-cfp-poster-showcase/

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Duke Electronic Health Records Study Design Workshop (EHR-SDW) 2023

Duke AI Health is pleased to announce the Duke Electronic Health Records Study Design Workshop (EHR-SDW) 2023. The workshop will be offered December 4th through 8th as a virtual five-day class that provides foundational lectures and hands-on studios on the fundamentals of working with and designing EHR based studies. The EHR-SDW is targeted toward individuals interested in learning about how to work with and conduct studies using electronic health records (EHR) data. EHR data are a widely available form of real-world data that have become standard in studies ranging from clinical trials, comparative effectiveness, risk prediction, and population health. The EHR-SDW will introduce the components of EHR data and introduce considerations for design of effective studies. In addition to didactic lectures, participants will get hands-on experience in working with publicly available tools to facilitate EHR studies (e.g., RxNorm, CCS codes, geocoding) as well as feedback on effective study designs that they will work on. The course will be conducted virtually via Zoom. This workshop is offered through Duke AI Health’s Health Data Science (HDS) program and builds on the success of the Electronic Health Records Study Design Workshop held in December 2022 and highly successful Machine Learning Schools, with 12 events held since 2017. The Duke Machine Learning Schools have reached hundreds of participants from academia and industry and including international audiences at the SingHealth/Duke NUS Medical School and the Duke Kunshan University campus. Our 2022 Duke Machine Learning Summer School attracted 140 participants from around the world, representing 41 universities, institutes, and corporations.

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Duke AI Health’s Nicoleta Economou talks guidelines & guardrails for responsible health AI development in AIMed “Champions” interview

Nicoleta Economou-Zavlanos, PhD, the director of Governance and Evaluation of health AI systems at Duke AI Health, was recently interviewed by AIMed’s Gemma Lovegrove for their AI Champions Interview Series, which highlights key thought leaders in the AI space. During the interview, Dr. Economou underscored the importance of incorporating fairness, transparency, and inclusivity throughout the entire process of health AI development, implementation, and monitoring.

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CHI Conference on Artificial Intelligence and the Future of Digital Healthcare

The Connected Health Initiative (CHI) is hosting an in-person conference titled ‘Artificial Intelligence and the Future of Digital Healthcare at the Crossroads’ on September 26, 2023, at the National Press Club in Washington, D.C., from 12:30 PM to 5:35 PM EDT. The event will delve into the profound impact of AI systems on healthcare, offering potential for improved outcomes, cost savings, and a shift towards proactive disease prevention. Duke AI Health Director Michael Pencina, PhD, ABCDS Director Nicoleta Economou-Zavlanos, PhD, and AI Health Equity Scholar Michael Cary, PhD, RN, will be presenting the Algorithm-Based Clinical Decision Support (ABCDS) Oversight framework at the conference, touching upon the program’s design, implementation and strategies for bias mitigation and ensuring health equity. The CHI conference aims to foster a vital public dialogue on the state of health AI, proactive approaches by leading organizations to address AI efficacy, and the government’s role in managing AI’s risks and opportunities in healthcare.

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Duke AI Health Director Michael Pencina Named Duke Health’s First Chief Data Scientist

Michael Pencina, PhD, vice dean for data science, professor of biostatistics and bioinformatics at Duke University School of Medicine, and director of Duke AI Health, has been named Duke Health’s first chief data scientist. Executive Vice President for Health Affairs and Dean Mary E. Klotman, MD, and Duke University Health System Chief Executive Officer Craig Albanese, MD, MBA, announced Pencina’s appointment. “In the current era of rapid expansion of AI and data science, we created this new role in recognition of the need for a well-articulated strategy for Duke Health that spans and connects both our academic and our clinical missions,” Klotman and Albanese said in their announcement.

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Flyer for the event

Please join us for a lunch and learn on September 19

Large language models (LLM) are powering amazing recent innovations in generative AI such as ChatGPT. Although their capabilities may seem like magic, behind these technologies are concepts that anyone can understand.

Please join us on Tuesday, September 19 for a lunch and learn as Larry Carin provides a math-free, intuitive explanation of how LLMs work. Dr. Carin will introduces participants to the deep-learning technology that has revolutionized the capacity of machines to perform language translation, to answer questions posed for given text, and to generate (synthesize) text that is near human-generated quality.

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