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Creating a collaborative ecosystem and robust infrastructure to enable AI to improve the field of Radiology and improve patient outcomes.
Artificial Intelligence has the power to truly transform radiological practice. The benefits of machine learning and deep neural networks in identifying disease earlier and more accurately is irrefutable. The integration of this technology at scale is, however, more challenging. How do we invest in building the necessary frameworks to validate these tools in the clinical setting? How do we ensure we are working in unison as an industry and not in a siloed and duplicative fashion. How do we ensure we maintain physician oversight/domain expertise when these tools are being developed?

Topics to be discussed will include

  • The need for unbiased Ground Truth Data
  • Overhaul of IT infrastructure within the healthcare system at large.
  • Patient privacy/protection issues
  • Develop comprehensive partnerships between clinicians with the vendor community to develop tools of clinical utility and usability
  • How do we speed up research without putting scientific integrity at risk. Is there a hybrid model?



John Quackenbush PhD

Henry Pickering Walcott Professor of Computational Biology and Bioinformatics Chair, Department of Biostatistics

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Neil Tenenholtz

Director of Machine Learning at the MGH & BWH Center for Clinical Data Science

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Neil Tenenholtz is the Director of Machine Learning at the MGH & BWH Center for Clinical Data Science, where his responsibilities include the training of novel deep learning models for clinical diagnosis, the development of robust infrastructure for their deployment into a clinical setting, and the creation of tooling to facilitate these processes. Prior to joining the Center, Neil was a Senior Research Scientist at Fitbit where he leveraged machine learning to improve human wellness at scale


Sara Gerke is the Research Fellow, Medicine, Artificial Intelligence, and Law, at the Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School. She oversees the day-to-day work of the Center’s Project on Precision Medicine, Artificial Intelligence, and the Law (PMAIL), including conducting law, policy, and ethics research; drafting reports and recommendations; and coordinating the Center's efforts with collaborators at the Center for Advanced Studies in Biomedical Innovation Law (CeBIL) at the University of Copenhagen as well as other partners.

Before joining the Petrie-Flom Center, Sara was employed as General Manager of the Institute for German, European and International Medical Law, Public Health Law and Bioethics of the Universities of Heidelberg and Mannheim (IMGB) in Germany. She was also the Co‑Investigator of an interdisciplinary project sponsored by the German Federal Ministry of Education and Research. This project, known as “ClinhiPS”, analyzed the clinical application of human induced pluripotent stem cells in Germany and Austria from a scientific, ethical and comparative legal perspective.


Esteban Rubens

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Esteban Rubens serves as the Global Principal for Enterprise Imaging at Pure Storage, where he is responsible for Pure's solutions, strategy, market development and thought leadership in that area of Healthcare. In addition to the traditional areas of Enterprise Imaging he focuses on the intersection of AI and medical imaging, with a particular emphasis on the role that IT infrastructure plays on both research and translational applications. Esteban has almost 20 years of experience in the storage industry, and over 15 years of experience working in the healthcare technology sector. He held several roles at FUJIFILM Medical Systems, Sandial Systems, Platypus Technology, and other storage companies.

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