HDS

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

Screencapture from the video showing pathology images

Highlight Video from Fall Digital Pathology Workshop

Last fall AI Health held an in-person workshop designed to give hands-on experience in working with medical digital pathology images using machine learning. See highlights from the afternoon in a video created by our partners in the Center for Computational Thinking. The concept of “do machine learning in just one afternoon!” was very successful, and we appreciate the participation from all those who attended. We are currently working to design more such studios, and please join our mailing list if you’d like to be notified for upcoming events.

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December Poster Showcase Highlights Research of 16 Students and Fellows

Duke AI Health’s HDS research and education hub held a successful Poster Showcase on December 6, 2022, featuring the work of 16 students and fellows. Hosted by Ricardo Henao, PhD, and Shelley Rusincovitch, MMCi, the presenters included members of the HDS fall 2022 student cohort, fellows in the AI Health Data Science Fellowship program, as well as members of AI Health’s Spark Imaging Initiative and Duke Biostatistics & Bioinformatics’s BCTIP program.

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Electronic flyer with abstract blue and white vector graphic advertising the Duke AI Health Electronic Health Records Study Design Workshop, December 5-9, 2022. Web page contains a full description of course offering, registration information, and instructors. Registration open to all (QR code included on flyer).

Creating a Successful Electronic Health Record (EHR) Study Design Workshop

Congratulations to AI Health Faculty Council member Ben Goldstein, PhD, and Duke Children’s Health & Discovery Initiative Director Jillian Hurst, PhD, for their success in leading the Electronic Health Record (EHR) Study Design Workshop from December 5-9, 2022. The course was offered as a virtual 5-day class providing foundational lectures and hands-on studios on the fundamentals of working with, and designing EHR-based studies. The inaugural workshop generated a great deal of enthusiasm and every seat in the course was filled within 6 weeks of course announcement.

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Duke AI Health Hosts December EHR Study Design Workshop

Duke AI Health is pleased to announce the Duke Electronic Health Records Study Design Workshop (EHR-SDW) 2022. The workshop will be offered in December 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. This workshop is offered through Duke AI Health’s Health Data Science (HDS) program and builds on the success of our highly successful Machine Learning Schools, with 11 events held since 2017.

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Image from the CAMELYON16 ISBI challenge on cancer metastasis detection: https://camelyon16.grand-challenge.org/Data/

AI Health Data Studio: Hands-On Digital Pathology

This in-person workshop presented by Ricardo Henao, PhD; Associate Professor, Department of Biostatistics and Bioinformatics; Chief AI Scientist, Duke AI Health, Akhil Ambekar, MS; Fellow, AI Health Data Science Fellowship Program, with Shelley Rusincovitch, MMCi; Managing Director, Duke AI Health, will give you hands-on experience in working with medical digital pathology images using machine learning. Our use case will be in whole slide images of lymph node sections. We will use the CAMELYON16 dataset (https://camelyon16.grand-challenge.org/), which consists of 400 hematoxylin and eosin-stained whole-slide images. During the workshop, you will learn how to retrieve, manage, and process these images, then apply a machine learning model based on a neural network architecture to classify image regions as normal or malignant. The techniques you learn will also be broadly applicable to other types of medical imaging.

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Call for Student Applications: AI Health’s Fall 2022 HDS Research Program

We invite Duke students to apply for the Health Data Science (HDS) fall research program. This competitive program, based in Duke AI Health, is designed to allow students who have previous experience in data science to continue their engagement with substantive applied projects. The HDS Research Program offers Duke students, both undergraduate and graduate, the opportunity to be a part of research teams applying advanced machine learning (deep learning) to important areas of medicine. Participating students will be mentored by leading Duke faculty involved in data science research, often with guidance by practicing clinicians. The fall will culminate in a showcase session where student teams will present their results.

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Duke Machine Learning Summer School 2022

The Duke+Data Science program is pleased to announce the Duke Machine Learning Summer School 2022, offered in June as a live five-day class that provides lectures on the fundamentals of machine learning. The curriculum in the MLSS is targeted to individuals interested in learning about machine learning, with a focus on recent deep learning methodology. The MLSS will introduce the mathematics and statistics at the foundation of modern machine learning, and provide context for the methods that have formed the foundations of rapid growth in artificial intelligence (AI).

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Call for Student Applications: HDS Summer 2022 Research Program​

We invite Duke students to apply for the Health Data Science (HDS) summer research program. This competitive program, based in Duke AI Health, is designed to allow students who have previous experience in data science to continue their engagement with substantive applied projects. The Advanced Machine Learning Projects in Health Data Science offers Duke students, both undergraduate and graduate, the opportunity to be a part of research teams applying advanced machine learning (deep learning) to important areas of medicine. Participating students will be mentored by leading Duke faculty involved in data science research, often with guidance by practicing clinicians. The summer will culminate in a showcase session where student teams will present their results.

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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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