Radiology's Dr. Michael Do honored as early career investigator
Dr. Huy (Michael) Do, a post-doctoral fellow with Radiology and Imaging Sciences, was recognized in February 2020 as a prominent early career investigator by the Academy for Radiology and Biomedical Imaging Research. He is one of 35 investigators in the Academy's 2020 class of the Council of Early Career Investigators in Imaging. The award is sponsored by the Society for Imaging Informatics in Medicine (SIIM) whose mission is advancing imaging informatics through education, research and innovation.
Do earned his M.D. degree from the George Washington University School of Medicine and Health Sciences with a scholarly concentration in research in May 2018, and came to the National Institutes of Health as an NIH Intramural Research Training Award post-doctoral fellow in June 2018.
Do's research in the NIH Clinical Centers Radiology and Imaging Sciences department focuses on utilizing artificial intelligence (AI) and imaging informatics to develop clinical solutions that enhance quantitative capabilities and workflow efficiency in radiology.
For his efforts in leading an important project, Do was the 2019 recipient of the New Investigator Travel Award by SIIM for his work with mentor Dr. Les Folio, lead radiologist for Computed Technology, on "Simulated Artificial Intelligence Workflow Improves Report Value in Clinical Trials While Saving Radiologists Time."
A subsequent manuscript on their research was accepted and published in the special AI edition of Academic Radiology in January 2020.
Folio describes Do's research impact and its advances on patient care, "With increasingly higher volumes of imaging exams ordered by referring clinicians, optimization of radiology workflows is essential to maintain and improve upon standards of care for our patients. As my post-doctoral fellow, Do has led numerous research projects that have been presented at national conferences with resultant publications. Through application of emerging technologies in AI and informatics, these efforts involve finding solutions to prevalent issues in our healthcare system, such as lack of interoperability between health information systems. He has also been integral in our clinical radiology workflow by measuring metastatic lesions in cancer clinical trial patients to enhance radiologist efficiency in locating key imaging findings and improve worklist prioritization through earlier detection of critical findings, simulating what AI can do in radiology and ultimately providing better patient care."
As a member of the 2020 CECI2 class, Do planned to present his research at the 11th Annual Medical Imaging Technology Showcase, which was originally scheduled to meet in Washington, DC May 2020 but has now been rescheduled to meet June 2021 in accordance with the CDC's guidance to help prevent the spread of COVID-19. Do and the other members of the 2020 class will now serve as the class of 2021.
- Mickey Hanlon