Join us for a panel on Behavioral XR on Thursday, June 3rd from 9:00 – 10:30 am PDT. The event will start with a one-hour panel discussion featuring Dr. Elizabeth McMahon, a psychologist with a private practice in California; Sarah Hill of Healium, a company developing XR apps for mental fitness based in Missouri; Christian Angern of Sympatient, a company developing VR for anxiety therapy based in Germany; and Marguerite Manteau-Rao of Penumbra, a medical device company based in California. This panel will be moderated by Dr. Walter Greenleaf of Stanford’s Virtual Human Interaction Lab (VHIL) and Dr. Christoph Leuze of the Stanford Medical Mixed Reality (SMMR) program. Immediately following the panel discussion, you are also invited to a 30-minute interactive session with the panelists where questions and ideas can be explored in real time.
Register here to save your place now! After registering, you will receive a confirmation email containing information about joining the meeting.
Please visit this page to subscribe to our events mailing list.
Sponsored by Stanford Medical Mixed Reality (SMMR)
Molecular Imaging in Neuroscience – MIPS Mini-Retreat
Hosted by: Dr. Michelle L. James, PhD
Sponsored by: Department of Radiology, Molecular Imaging Program at Stanford
The MIPS Mini-retreat series brings together members of the MIPS and greater School of Medicine community to discuss current opportunities for research and collaborations. During each mini-retreat we will discuss a different topic and we invite all those interested to attend. The mini-retreats are roughly two hours in length with ample time for discussion throughout. We hope you can join us and spark new collaborations!
Zoom Webinar Information
Webinar URL: https://stanford.zoom.us/j/92903233643
Dial: US: +1 650 724 9799 or +1 833 302 1536 (Toll Free)
Webinar ID: 929 0323 3643
Passcode: 146018
Tentative Agenda (all times are in PST)
8:00-8:05 AM – Opening Remarks – Michelle James, PhD
8:05-8:55 AM – Overview and Imaging-based Collaboration: Department of Neurology, Neurosurgery, Pathology, Psychiatry, and Nuclear Medicine (Frank M. Longo, MD, PhD, Michael Lim, MD, Thomas Montine, MD, PhD, Victor G. Carrión, MD, and Guido Davidzon, MD)
8:55-9:20 AM – Faculty Introductions: All interested MIPS faculty on the call give a 2-minute introduction including their interest in collaborating with Neurology, Pathology, Neurosurgery, and/or Psychiatry and Behavioral Sciences departments.
9:20-9:40 AM – Recent center proposals and possible mechanisms: UDALL Collaboration – Michelle James, PhD and Kathleen Poston, MD, MS
9:40-10:00 AM – Discussion – Moderated by: Michelle James, PhD and Katherine Ferrara, PhD
Radiology Department-Wide Research Meeting
• Research Announcements
• Mirabela Rusu, PhD – Learning MRI Signatures of Aggressive Prostate Cancer: Bridging the Gap between Digital Pathologists and Digital Radiologists
• Akshay Chaudhari, PhD – Data-Efficient Machine Learning for Medical Imaging
Location: Zoom – Details can be found here: https://radresearch.stanford.edu
Meetings will be the 3rd Friday of each month.
Hosted by: Kawin Setsompop, PhD
Sponsored by: the the Department of Radiology
Stanford AIMI Director Curt Langlotz and Co-Directors Matt Lungren and Nigam Shah invite you to join us on August 3 for the 2021 Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI) Symposium. The virtual symposium will focus on the latest, best research on the role of AI in diagnostic excellence across medicine, current areas of impact, fairness and societal impact, and translation and clinical implementation. The program includes talks, interactive panel discussions, and breakout sessions. Registration is free and open to all.
Also, the 2nd Annual BiOethics, the Law, and Data-sharing: AI in Radiology (BOLD-AIR) Summit will be held on August 4, in conjunction with the AIMI Symposium. The summit will convene a broad range of speakers in bioethics, law, regulation, industry groups, and patient safety and data privacy, to address the latest ethical, regulatory, and legal challenges regarding AI in radiology.
Regina Barzilay, PhD
School of Engineering Distinguished Professor for AI and Health
Electrical Engineering and Computer Science Department
AI Faculty Lead at Jameel Clinic for Machine Learning in Health
Computer Science and Artificial Intelligence Lab
Massachusetts Institute of Technology
Abstract:
In this talk, I will present methods for future cancer risk from medical images. The discussion will explore alternative ways to formulate the risk assessment task and focus on algorithmic issues in developing such models. I will also discuss our experience in translating these algorithms into clinical practice in hospitals around the world.
MIPS Seminar Series: Predicting and Preventing Fetal and Neonatal Pathology: Looking Back and Looking Forward
David K. Stevenson, MD
The Harold K. Faber Professor of Pediatrics, Senior Associate Dean, Maternal and Child Health and Professor, by courtesy, of Obstetrics and Gynecology
Lucile Packard Children’s Hospital
Zoom Webinar Details
Webinar URL: https://stanford.zoom.us/s/94584828060
Dial: +1 650 724 9799 or +1 833 302 1536
Webinar ID: 945 8482 8060
Passcode: 481874
12:00pm – 12:45pm Seminar & Discussion
RSVP Here
ABSTRACT
The importance of minimally invasive technologies for interrogating the fetus and newborn, as well as of knowing where a biologic system is headed, not just where it has been, when trying to predict and prevent acquired diseases, will be discussed. Examples of such technologies, such as trace gas analysis and optical reporting of biologic phenomena, and their application to model systems and the human newborn will be presented. The role of advanced computational approaches for the integration and interpretation of large amounts of data derived from these new measurement tools will be emphasized.
ABOUT
Dr. David K. Stevenson is the Harold K. Faber Professor of Pediatrics and has made many impactful contributions to the field of neonatology and pediatrics, including his seminal studies on neonatal jaundice, bilirubin production and heme oxygenase biology. As a neonatologist, his research has focused primarily on neonatal jaundice and more recently on the causes of preterm birth and its prevention. He has held numerous leadership roles at Stanford University School of Medicine, including Vice Dean and Senior Associate Dean for Academic Affairs. He is currently the Senior Associate Dean for Maternal & Child Health, the Co-Director of the Stanford Maternal & Child Health Research Institute, and the Principal Investigator for the March of Dimes Prematurity Research Center at Stanford University. Dr. Stevenson has received many awards, including the Virginia Apgar Award, which is the highest award in Perinatal Pediatrics, the Joseph W. St. Geme, Jr. Leadership Award from the Federation of Pediatric Organizations, the Jonas Salk Award for Leadership in Prematurity Prevention from the March of Dimes Foundation, and the John Howland Medal and Award, the highest award in academic pediatrics. He has served as the President of the American Pediatric Society. In recognition of his achievements, Dr. Stevenson is a member of the National Academy of Medicine.
Hosted by: Katherine Ferrara, PhD
Sponsored by: Molecular Imaging Program at Stanford & the Department of Radiology
Keynote:
Self-Supervision for Learning from the Bottom Up
Why do self-supervised learning? A common answer is: “because data labeling is expensive.” In this talk, I will argue that there are other, perhaps more fundamental reasons for working on self-supervision. First, it should allow us to get away from the tyranny of top-down semantic categorization and force meaningful associations to emerge naturally from the raw sensor data in a bottom-up fashion. Second, it should allow us to ditch fixed datasets and enable continuous, online learning, which is a much more natural setting for real-world agents. Third, and most intriguingly, there is hope that it might be possible to force a self-supervised task curriculum to emerge from first principles, even in the absence of a pre-defined downstream task or goal, similar to evolution. In this talk, I will touch upon these themes to argue that, far from running its course, research in self-supervised learning is only just beginning.
MIPS Seminar Series: Title TBA
Steven Paul Poplack, MD
Professor of Radiology (Breast Imaging)
Stanford University Medical Center
Location: Coming soon!
12:00pm – 12:45pm Seminar & Discussion
RSVP: Coming soon!
ABSTRACT
Coming soon!
ABOUT
Coming soon!
Hosted by: Katherine Ferrara, PhD
Sponsored by: Molecular Imaging Program at Stanford & the Department of Radiology
Saeed Hassanpour, PhD
Associate Professor of Biomedical Data Science
Associate Professor of Epidemiology
Associate Professor of Computer Science
Dartmouth Geisel School of Medicine
Deep Learning for Histology Images Analysis
Abstract:
With the recent expansions of whole-slide digital scanning, archiving, and high-throughput tissue banks, the field of digital pathology is primed to benefit significantly from deep learning technology. This talk will cover several applications of deep learning for characterizing histopathological patterns on high-resolution microscopy images for cancerous and precancerous lesions. Furthermore, the current challenges for building deep learning models for pathology image analysis will be discussed and new methodological advances to address these bottlenecks will be presented.
About:
Dr. Saeed Hassanpour is an Associate Professor in the Departments of Biomedical Data Science, Computer Science, and Epidemiology at Dartmouth College. His research is focused on machine learning and multimodal data analysis for precision health. Dr. Hassanpour has led multiple NIH-funded research projects, which resulted in novel machine learning and deep learning models for medical image analysis and clinical text mining to improve diagnosis, prognosis, and personalized therapies. Before joining Dartmouth, he worked as a Research Engineer at Microsoft. Dr. Hassanpour received his Ph.D. in Electrical Engineering with a minor in Biomedical Informatics from Stanford University and completed his postdoctoral training at Stanford Center for Artificial Intelligence in Medicine & Imaging.
MIPS Seminar Series: Title TBA
Matthew Bogyo, PhD
Professor of Pathology and of Microbiology and Immunology and, by courtesy, of Chemical and Systems Biology
Stanford University
Location: Coming soon!
12:00pm – 12:45pm Seminar & Discussion
RSVP: Coming soon!
ABSTRACT
Coming soon!
ABOUT
Dr. Bogyo received a B.Sc. degree in Chemistry from Bates College in 1993 and a Ph.D. in Biochemistry from the Massachusetts Institute of Technology in 1997. After completion of his degree he was appointed as a Faculty Fellow in the Department of Biochemistry and Biophysics at the University of California, San Francisco. Dr. Bogyo served as the Head of Chemical Proteomics at Celera Genomics from 2001 to 2003 while maintaining an Adjunct Faculty appointment at UCSF. In the Summer of 2003 Dr. Bogyo joined the Department of Pathology at Stanford Medical School and was appointed as a faculty member in the Department of Microbiology and Immunology in 2004. His interests are focused on the use of chemistry to study the role of proteases in human disease. In particular his laboratory is currently working on understanding the role of cysteine proteases in tumorgenesis and also in the life cycle of human parasites and bacterial pathogens. Dr. Bogyo currently serves on the Editorial Board of Biochemical Journal, Cell Chemical Biology, Molecular and Cellular Proteomics and is an Academic Editor at PLoS One. Dr. Bogyo is a consultant for several biotechnology and pharmaceutical companies in the Bay Area and is a founder and board member of Akrotome Imaging and Facile Therapeutics.
Hosted by: Katherine Ferrara, PhD
Sponsored by: Molecular Imaging Program at Stanford & the Department of Radiology