Erich Senin Huang

에릭 세닌 황

에릭 세닌 황은 듀크대학교 헬스데이터사이언스센터 공동 디렉터다. 그는 듀크대학교에서 암 전달경로(cancer signalling pathways)를 머신러닝을 활용해서 모델링하는 논문으로 박사학위를 받았다. 박사학위를 받은 후에는 듀크대학교의 Surgery Residency Program에서 임상의학 훈련을 시작했다. 2011년에는 워싱턴 시애틀의 Sage Bionetworks의 암연구 세터장으로 부임해 오픈사이언스(Open Science)와 오픈 암데이터 사이언스(open cancer data science)를 위한 클라우드 플랫폼을 구축했다. 그곳에서 그는 API 개발을 위한 Sloan Foundation의 지원을 받았다.

Erich Senin Huang

Erich Huang, MD, PhD, is Co-Director of Duke Forge. Dr. Huang received his PhD and MD degrees from Duke University. There, his doctoral work comprised applying machine learning tools to model cancer signaling pathways. Moving into the world of clinical medicine, Dr. Huang trained in Duke’s Surgery Residency Program. After completing his Chief Residency, Dr. Huang joined the faculty of Duke's Department of Surgery. In 2011, he was recruited to be Director of Cancer Research by Sage Bionetworks in Seattle, Washington. There, he led efforts in building a cloud-based platform and tools for Open Science and open cancer data science challenges. There he was funded by the Sloan Foundation for developing scientific provenance APIs. Extensions of that work were funded by the NIH’s Big Data to Knowledge program when Dr. Huang was recruited to be the first faculty member in Duke’s Division of Translational Biomedical Informatics. He is a Sidney Kimmel Cancer Research Foundation Translational Scholar Awardee, an IBM Faculty Awardee, and a Burroughs Wellcome Fund Regulatory Science Awardee.



Summary

In the age of the “electronic health record”, many of the things that we thought would be straightforward remain hard. Physicians and nurses spend a great deal of their time both caring for their patients and entering data, yet it seems that most of these data are not leveraged to the degree they ought to be. I will be presenting projects at Duke that demonstrate the “art of the possible”. We have developed machine learning workflows that are actively being used in the care of patients by essentially providing a risk-based “air traffic control” for our entire Accountable Care Organization. This has required pragmatism, robust data science capabilities, and tremendous collaborative labor of teams including, physicians, nurses, social workers, pharmacists, biostatisticians, bioinformaticians, and data scientists. This is just an example of many projects that we are undertaking. What these projects also reveal is our need to build “ecosystems” that allow new ideas to take root and thrive. This is an alternative model to the traditional healthcare IT world where most systems are siloed and different to integrate. For healthcare to live up to the promise of a 4th Industrial Revolution, it is projects like these which reveal possibility and demonstrate to those of us in healthcare how to build and support ecosystems where ideas and implementation are the rate-limiting steps, rather than the technology.