23rd INTERNATIONAL CONFERENCE ON MEDICAL IMAGE
COMPUTING & COMPUTER ASSISTED INTERVENTION
4-8 OCTOBER 2020

MICCAI 2020 INDUSTRY SESSION

Date:
6 October 2020
Time:
12:00 - 13:30 UTC

Healthcare Accessibility: are technologies helping?

Artificial Intelligence is shaping to be one of the most transformative technologies in the 21st century. Healthcare systems continuously explore ways to provide wider access to care and better care to all individuals. However, the wide range of complex and unique technologies that form the structure of such systems are highly regulated, require skilled professionals and present significant challenges in achieving this goal. In spite of the many barriers, AI has already affected a number of medical domains most prominently radiology and pathology. The quality of the solutions developed within the research community have achieved human level performance and in specific cases surpassed the medical experts' performance. This power combined with point-of-care medical devices, 5G network coverage and cloud computing chart unprecedented territories. Do these solutions present the opportunity to provide better care and wider access to care with sustainable costs, and what are the pitfalls?

Please join us to hear from leaders in Industry, government and healthcare. The session will include short presentations followed by a panel discussion with interactive Q&A with audience.


Speakers

Dr. Patricia Garcia
Dr. Patricia Garcia

Dr. Patricia J. García is a Professor at the School of Public Health at Cayetano Heredia University (UPCH) in Lima-Peru. She is the former Minister of Health of Peru, Dean of the School of Public Health at UPCH, and former Chief of the Peruvian National Institute of Health (INS). As Dean of the School of Public Health at UPCH, she secured funding for over $1M from Grand Challenges Canada and the Bill & Melinda Gates Foundation. She is recognized as a leader in Global Health. Has been member of the PAHO Foundation Technical Advisory Group (FTAG), board member of the Consortium of Universities in Global Health and President of the Latin American Association Against STDs (ALACITS). She is affiliate Professor of the Department of Global Health, at University of Washington and of the School of Public Health at Tulane University. She is actively involved in research and training in Global health, Reproductive health, STI/HIV, HPV and medical informatics. She was appointed member of the United States National Academy of Medicine, becoming the first Peruvian professional with such a distinction.

Dr. Mikhal Sofka
Dr. Mikhal Sofka

Michal Sofka is currently leading the deep learning team at Hyperfine Research in New York. Hyperfine created an innovative point-of-care MRI, that wheels directly to the patient's bedside, plugs into a standard electrical wall outlet, and is controlled via a wireless tablet. Michal is on a mission to develop algorithms that improve images and run on the scanner and tools for image interpretation that run in the cloud. Hyperfine is a member of 4Catalyzer, a group of technological startups focused on developing new types of sensors and pairing them with deep learning to get a new window into biology and medicine. Until 2017, Michal worked on automated measurements and scan acquisition assistance for the iQ, new hand-held ultrasound device developed by Butterfly Network, another 4Catalyzer company. Before joining 4Catalyzer, Michal was a senior technical leader in the Cisco's Cognitive Threat Analytics team in Prague, Czech Republic. Prior to Cisco, Michal worked as a senior scientist and project leader at Siemens Corporate Research, top healthcare industrial R&D lab in Princeton, New Jersey. He received the MS degree in Electrical Engineering from Union College and MS and PhD degrees in Computer Science from the Rensselaer Polytechnic Institute (RPI).

Dr. Michal Rosen-Zvi
Dr. Michal Rosen-Zvi

Dr. Rosen-Zvi is a Director of health informatics at IBM Research and a visiting professor at the Faculty of Medicine, The Hebrew University. At IBM Research she leads the research strategy of a worldwide team who are experts in AI applied to health data and she is the local senior manager of the IBM Research Haifa department who focuses on deep learning, machine learning and casual inference technologies applied to patients data. Michal holds a PhD in computational physics and completed postdoctoral studies at UC Berkeley, UC Irvine, and the Hebrew University in the area of Machine Learning. She joined IBM Research in 2005 and has since led various projects in the area of machine learning and healthcare. Michal has published more than 40 peer-reviewed papers. She serves at various boards and committees such as the Israeli national digital health committee and the Impact Advisory Committee of the 8400 health network.io Michal

Ali Kamen, PhD
Ali Kamen, PhD

Ali Kamen is the Principal for Artificial Intelligence and Digital Innovation at Siemens Healthineers. He received BSc in EE and MSc in BME from the Sharif University of Technology. He received a PhD in ECE from the University of Miami. After graduation, he joined Siemens Corporate Research in Princeton, NJ, where he has been leading technology development teams in personalized healthcare and image-guided procedures. Currently, he leads initiatives in translating artificial intelligence-based technologies to differentiated value-creating clinical products. Additionally, Dr. Kamen leads active collaborations with several universities, including the University of Pennsylvania, Cleveland Clinic, Harvard Medical School, Johns Hopkins, and the University of Iowa, with more than $5M awarded from NIH-funded grants. He has more than 100 refereed publications (with h-Index 43), and more than 100 US and international patents (granted and pending) primarily in the areas of medical image computing, computational modeling, and image-guided procedures. He is recognized as Siemens Inventor of the Year in 2015. He is also a Fellow of the American Institute for Medical and Biological Engineers.

Dr. Mona Flores
Dr. Mona Flores

Mona is the Global Head of Medical AI at NVIDIA. She brings a unique perspective with her varied experience in clinical medicine, medical applications, and business. She is a board certified cardiac surgeon and the previous Chief Medical Officer of a digital health company.
She holds an MBA in Management Information Systems, and has worked on Wall Street. Her ultimate goal is the betterment of medicine through AI.

Dr. Eyal Gura
Dr. Eyal Gura

Mr Gura is the Co-Founder and Chairman of Zebra Medical Vision, a deep learning medical imaging company that will enable scalable healthcare for the 2 billion people to join the middle class by 2025. Eyal is an Angel investor and previously venture capitalist with Pitango Venture Capital, the largest venture capital fund in the Middle East. Formerly, Co-Founder: PicScout (acquired by Getty Images); PicApp (acquired by Ybrant Digital); The Gifts Project (acquired by eBay). In his non profit capacity Eyal is a Board member at Latet and at IDC university And a Founding Member of Tovanotb.org and a faculty member at IDC's Zell entrepreneurship program. Eyal is a graduate of the Wharton Business School of the University of Pennsylvania and was named a Young Global Leader by the World Economic Forum.

Dr. Ying Chi
Dr. Ying Chi

Dr Ying Chi is a premier algorithm expert with Alibaba DAMO Academy AI Center for Healthcare Intelligence. She received her Ph.D. in Bioengineering from Imperial College London, UK, followed by postdoctoral training at the Institute of Biomedical Engineering, Oxford University, UK. Prior to Alibaba, she worked as a Manager for Medical AI at Siemens. Dr. Chi has published more than 80 journal and conference papers, and book chapters. Her doctoral thesis was awarded the Best Paper at the Annual Meeting of the European Magnetic Resonance Society, the Old Centralien's Innovation Award from the City of London, and the Imperial College Excellence in Innovation Award. After joining Alibaba, she has been leading a team at the AI Center of Alibaba DAMO Academy where her research has won several international challenges including the MICCAI LiTS Liver and Liver Nodule Segmentation. In response to the COVID-19 outbreak, her team at Alibaba has been developing various AI products (CT image analysis, whole-genome sequencing analysis, epidemic prediction, response to questions based on knowledge graphs, and video translation on a knowledge exchange platform). Part of the code developed by her group for CT image analysis is archived with the National Science and Technology Museum of China. The products developed by her team are deployed in over 90 hospitals in Japan. Her current research focus is on medical imaging, picture analysis, natural language processing, gene, protein, and pharmaceutical development.

Dr. Charles Kahn
Dr. Charles Kahn

Dr. Charles Kahn is Professor and Vice Chairman of Radiology at the University of Pennsylvania. He earned his Bachelor of Arts in Mathematics at the University of Wisconsin, his M.D. at the University of Illinois, and completed radiology residency at the University of Chicago. He earned a Master of Science in Computer Sciences from the University of Wisconsin during a sabbatical in 2003. He is a Board-certified, practicing radiologist with expertise in body CT and ultrasound. Professional interests include health services research and AI (especially knowledge representation and probabilistic reasoning). He served two terms as Co-chair of the DICOM Standards Committee, and was President of the American Roentgen Ray Society. Honors include the Gold Medal of the American Roentgen Ray Society, Honorary Membership of the Italian Society of Medical Radiology (SIRM), and elected Fellowship of the American College of Radiology, the American College of Medical Informatics, and the Society for Imaging Informatics in Radiology. He is author of more than 120 scientific publications, has given more than 100 invited lectures, and serves as Editor of Radiology: Artificial Intelligence.

Dr. Alison O'Neil
Dr. Alison O'Neil

Alison O'Neil is a Senior Scientist in the AI Research Team at Canon Medical Research Europe and Honorary Research Fellow at the University of Edinburgh. She leads a team of scientists and research students working on machine learning techniques for healthcare applications for medical imaging, natural language processing, and electronic health record data. Her research has covered techniques for medical image registration, segmentation of anatomy and pathology, anatomical landmark detection, and more recently prediction of outcomes from clinical data and the extraction of semantic information from medical text. She is Associate Editor of the IEEE Journal of Biomedical and Health Informatics and was the main organiser of the ICLR 2020 "AI for Affordable Healthcare" workshop as well as co-presenting the ECCV 2020 tutorial on "Computer Vision for Medical Imaging Applications". She has multiple publications and patents in the domain of medical AI.