Posts – Page 8 – Duke AI Health

Article: Building Better Guardrails for Algorithmic Medicine

Recent years have seen growing interest in the use of artificial intelligence tools for healthcare applications, including diagnosis, risk prediction, clinical decision support, and resource management. Capable of finding hidden patterns within the enormous amounts of data that reside in patient electronic health records (EHRs) and administrative databases, these algorithmic tools are diffusing across the world of patient care. Often, health AI applications are accompanied by assurances of their potential for making medical practice better, safer, and fairer. The reality, however, has turned out to be more complex.

Article: Building Better Guardrails for Algorithmic Medicine Read More »

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.

December Poster Showcase Highlights Research of 16 Students and Fellows Read More »

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.

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

MITRE Grand Challenges Power Hour: Modeling Equitable AI in Digital Health

Join Duke AI Health Director Michael Pencina, PhD, as he takes part in discussions with expert panelists convened from government, industry and academia to discuss recent advances in health AI, including structural biological modeling, computer vision algorithms, and ethical frameworks for employing AI in healthcare. This virtual event, “Modeling Equitable AI in Digital Health,” is hosted by MITRE and will take place starting at 4:00 PM EST on Thursday, December 8, 2022.

MITRE Grand Challenges Power Hour: Modeling Equitable AI in Digital Health Read More »

Blog: My Cancer on MyChart

DCRI Science and Digital Officer Eric Perakslis, PhD, shares a deeply personal perspective on a recent federal mandate that expands patients’ access to data stored in their EHRs – but also carries its own potential for risks. In his essay, Dr. Perakslis combines the patient and tech expert viewpoints as he surveys the “lumpy, bumpy, imperfect progress” toward better data transparency while undergoing cancer diagnosis and treatment.

Blog: My Cancer on MyChart Read More »

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.

Duke AI Health Hosts December EHR Study Design Workshop Read More »

AI Health Data Science Fellowship Program Welcomes New Members

The AI Health Data Science Fellowship Program is a two-year training program focused on data science with healthcare applications, designed for early-career data scientists with strong backgrounds in quantitative disciplines. Launched in fall of 2019, the program currently has 5 fellows, 2 staff data scientists, and 5 alumni. The program recently came together in-person for lunch for the first time since the pandemic. They gathered to welcome 2 new members: new fellow Angel Huang and new Data Scientist, John Rollman.

AI Health Data Science Fellowship Program Welcomes New Members Read More »

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.

AI Health Data Studio: Hands-On Digital Pathology Read More »

Chief AI Health Scientist Ricard Henao Named Associate Professor

Duke AI Health congratulates Chief AI Health Scientist Ricardo Henao, PhD, on his promotion to the rank of Associate Professor in the Department of Biostatistics and Bioinformatics in the Duke University School of Medicine. Dr. Henao is a major presence in health data science at Duke, where his leadership and expertise in machine learning methods and implementation have made him a sought-after collaborator and instructor. “Dr. Henao is a major asset to Duke AI Health and to the larger Duke community,” said Michael Pencina, PhD, director of Duke AI Health and vice dean for data science at the School of Medicine. “We feel fortunate to be able to benefit from such a rare combination of talent and knowledge spanning research, application, and teaching.”

Chief AI Health Scientist Ricard Henao Named Associate Professor Read More »

Duke AI Health Director Michael Pencina Surpasses 100K Citations for Academic Research

Duke AI Health Director and Vice Dean for Data Science Michael J. Pencina, PhD, has achieved a major academic milestone: according to Google Scholar’s analytics, he has recently passed the 100,000 mark for academic citations of his work. Pencina, who in addition to his leadership role in Duke’s efforts to develop, evaluate, and implement ethical and equitable data science, has also worked extensively on the development and evaluation of risk prediction models and clinical trial designs.

Duke AI Health Director Michael Pencina Surpasses 100K Citations for Academic Research Read More »