A Primer on Biodefense Data Science and Technology for Pandemic Preparedness

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BLOG: “During the onset of an event such as the one we’re now experiencing, resilience is the key priority. Secure your systems and protect your family and business. Remember, cybercrime spreads just as easily from personal devices to work devices as viruses do between people. Biodefense may have previously been considered the domain of the military and antiterrorism experts, but all of us now have a potential role to play. Please consider lending your time and expertise.” – Eric D. Perakslis, PhD

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Duke Biomedical Engineers Find Heart Rate Measurements of Wearable Monitors Vary by Activity, Not Skin Color

Picture from story showing doctoral candidate Brinnae Bent and Duke Big Ideas Lab director Jessilyn Dunn at work on a project.

Biomedical engineers at Duke University have demonstrated that while different wearable technologies, like smart watches and fitness trackers, can accurately measure heart rate across a variety of skin tones, the accuracy between devices begins to vary wildly when they measure heart rate during different types of everyday activities. The study results appear online on February 10 in the journal NPJ Digital Medicine.

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Funding Opportunity: Research in Health Data Science

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In collaboration with Duke AI Health and Duke Forge, the Duke Department of Medicine is seeking proposals for research in health data science. This request for proposals is designed to fulfill two missions: 1) to grow Department of Medicine faculty involvement in health data science; and 2) to support research that will then be used to improve the quality of care for patients at Duke Health.

The Department is particularly interested in proposals that utilize data from the Duke University Health System. We plan to fund several 1-year awards.

The deadline for submitting proposals has been extended to 5:00 PM Eastern time, Thursday, April 30th, 2020.

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Now Accepting Applications for 2020 Health Data Science Postdoctoral Scholar

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Duke Forge, in collaboration with Duke AI Health, announces a new scholarship opportunity for research at the intersection of quantitative science and health. This program is open to postdoctoral researchers in quantitative science programs. This program funds innovative, strategic, and creative researchers to develop and apply new analytical tools to solve challenges in human health and the delivery of healthcare. Successful applicants will show evidence of outstanding research ability and strong interest in health data science.

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Introducing AI Health

Photograph of AI Health Co-Director Lawrence Carin, PhD, and Duke Forge and Duke Crucible Director Erich Huang, MD, PhD, introduce Duke AI Health at the Fall 2019 Duke Health Data Science Showcase.

Duke Vice President for Research Lawrence Carin, PhD, and Forge Co-Director Erich Huang, MD, PhD,  recently introduced AI Health, Duke’s new multidisciplinary, campus-spanning organization dedicated to enabling research into applications of artificial intelligence and machine learning in healthcare, and to effectively translating that research into techniques and technologies that will improve health outcomes for patients and communities. AI Health will also have a strong presence in education and workforce development as it builds training programs to equip students, quantitative scientists, and clinicians for a future that will increasingly be shaped by data science.

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+DS Student Showcase on December 4

The +DS program held a student showcase on Wednesday, December 4, 2019 from 4:30-6:00 PM in the Energy Hub Atrium (first floor of Gross Hall). More than 30 student posters were presented.

27 teams with 62 students presented from the +DS fall 2019 course POE 190.01/POE 790.01 “Introduction to Machine Learning Methods and Practice.” This mini-class has introduced students to machine learning methods that have become increasingly useful in practice, specifically deep learning and neural networks. The student have produced their end-of-semester projects with applications of machine learning to a problem of relevance to their field of study or major.

5 teams with 8 students presented from the +DS Advanced Projects. Students who have previously completed the +DS curriculum are eligible to apply for the Advanced Projects, typically structured as an independent study project, where they are mentored by experts in data science partnered within clinicians in areas of focus including dermatology, ophthalmology, pathology, radiology, and cardiology.

These +DS project-based learning teams offer Duke students, both undergraduate and graduate, the opportunity to be a part of teams applying advanced data science methods and machine learning to real-world problems, and as a means of learning the important field of machine learning in a manner that is accessible and adaptive to all Duke students.

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Data Science Showcase Highlights Duke Student Experiences

Students, faculty, and staff from across Duke recently assembled for the Data Science Student Showcase, held at the Gross Hall Atrium on the morning of April 25th. Put together by the +DS Projects in Medicine and the DCRI-Forge HDS Internship Program(link is external), the event served as a platform for students to present the projects that they have been immersed in during the spring semester.

“The students have an important opportunity to learn through these experiences,” said Lisa Wruck, PhD, director of the Center for Predictive Medicine, who delivered the introductory remarks at the event. “We appreciate the contributions of the mentors, program coordinators, and the hard work of the students themselves.”

The Showcase featured the efforts of nine students with the DCRI-Forge HDS Internship Program. Through brief “lightning talks,” they were able to highlight the methods and initial findings of their research. Twelve student teams with the +DS Projects in Medicine also presented posters about their applied projects, for a total of 71 student participants.

“It’s not just applying machine learning models, but also about having a more immersive experience with real data, provenance, and applications,” said Ricardo Henao, PhD, Duke Forge principal data scientist and assistant professor in the Department of Biostatistics and Bioinformatics, who provided the closing remarks. “With +DS, we establish a solid background in machine learning. Then with the HDS interns, we are addressing real problems and developing the pipeline.”

The +DS Projects in Medicine is an eight-month program where students get a chance to apply state-of-the-art deep learning technology to image analysis, with the goal of assisting clinicians in making decisions on diagnosis and delivery of care. During the fall 2018 semester, students received training in deep learning with a particular focus on image analysis, constituted via the online +DS learning modules and through complementary in-person learning experiences. Thirteen student teams were formed in the spring of 2019, mentored by leading Duke Faculty involved in data science research with areas of focus in dermatology, ophthalmology, pathology, radiology, and cardiology.

The HDS Internship Program is a partnership between the Duke Clinical Research Institute (DCRI) and Duke Forge. The projects that the interns are introduced to through the internship are part of the Forge Demonstration Program in which transdisciplinary teams use advanced data science methods to “demonstrate the art of the possible.” The HDS internship program is structured as a 17-month program with interns working under the direction of quantitative experts, paired with biostatistician staff mentors primarily from the Center for Predictive Medicine, and receiving dedicated technical and professional skills training.

“Our goal is to offer Duke students, both undergraduate and graduate, the important opportunity to be a part of research teams,” said Larry Carin, PhD, Duke University Vice Provost for Research.

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