Calendar

Oct
15
Thu
2020
StanfordMed LIVE - Disability Town Hall @ Virtual Event - See Description for Livestream Link
StanfordMed LIVE – Disability Town Hall
Oct 15 @ 12:00 pm – 1:00 pm Virtual Event - See Description for Livestream Link
StanfordMed LIVE - Disability Town Hall @ Virtual Event - See Description for Livestream Link

In honor of the 30th anniversary of the Americans with Disabilities Act and October as National Disability Employment Awareness Month, join the Stanford Medicine Abilities Coalition (SMAC) for a first of its kind StanfordMed LIVE event focused on disability. Now more than ever during the COVID-19 pandemic, disabilities, health conditions, and illness impact not only our patients but also all of us, both personally and as members of the Stanford Medicine community. Stanford Medicine leadership will share information, answer questions, and engage in a roundtable discussion about the state of disability at Stanford and how best to support faculty, staff, and students living with disability and chronic illness. We encourage our community to submit questions and comments here to be shared broadly with the Stanford Medicine community. The same link can be used to request any accommodations needed for the livestream. Additional information for the webcast itself will be sent out closer to the event.

Livestream link: https://livestream.com/accounts/1973198/events/9288854

Nov
18
Wed
2020
IBIIS & AIMI Seminar: Deep Tomographic Imaging @ Zoom: https://stanford.zoom.us/j/96731559276?pwd=WG5zcEFwSGlPcDRsOUFkVlRhcEs2Zz09
IBIIS & AIMI Seminar: Deep Tomographic Imaging
Nov 18 @ 12:00 pm – 1:00 pm Zoom: https://stanford.zoom.us/j/96731559276?pwd=WG5zcEFwSGlPcDRsOUFkVlRhcEs2Zz09

Ge Wang, PhD
Clark & Crossan Endowed Chair Professor
Director of the Biomedical Imaging Center
Rensselaer Polytechnic Institute
Troy, New York

Abstract:
AI-based tomography is an important application and a new frontier of machine learning. AI, especially deep learning, has been widely used in computer vision and image analysis, which deal with existing images, improve them, and produce features. Since 2016, deep learning techniques are actively researched for tomography in the context of medicine. Tomographic reconstruction produces images of multi-dimensional structures from externally measured “encoded” data in the form of various transforms (integrals, harmonics, and so on). In this presentation, we provide a general background, highlight representative results, and discuss key issues that need to be addressed in this emerging field.

About:
AI-based X-ray Imaging System (AXIS) lab is led by Dr. Ge Wang, affiliated with the Department of Biomedical Engineering at Rensselaer Polytechnic Institute and the Center for Biotechnology and Interdisciplinary Studies in the Biomedical Imaging Center. AXIS lab focuses on innovation and translation of x-ray computed tomography, optical molecular tomography, multi-scale and multi-modality imaging, and AI/machine learning for image reconstruction and analysis, and has been continuously well funded by federal agencies and leading companies. AXIS group collaborates with Stanford, Harvard, Cornell, MSK, UTSW, Yale, GE, Hologic, and others, to develop theories, methods, software, systems, applications, and workflows.

Apr
1
Thu
2021
SMMR Panel Discussion: Mixed Reality for Surgical Guidance @ Zoom
SMMR Panel Discussion: Mixed Reality for Surgical Guidance
Apr 1 @ 9:00 am – 10:30 am Zoom
SMMR Panel Discussion: Mixed Reality for Surgical Guidance @ Zoom

Mixed Reality for Surgical Guidance will take place on Thursday, April 1st from 9:00 – 10:30 am PDT.

The event will start with a one-hour panel discussion featuring Dr. Bruce Daniel of Stanford Radiology and the Stanford IMMERS Lab; Christoffer Hamilton of Brainlab, a surgical software and hardware leader in Germany; and Dr. Thomas Grégory of Orthopedic Surgery at the Université Sorbonne Paris Nord.

This panel will be moderated by Dr. Christoph Leuze of Stanford University and 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: https://stanford.zoom.us/meeting/register/tJcqf-GrqToiHNKL4D-5haRLowQylIwMEAve

Apr
10
Sat
2021
Stanford School of Medicine's 2nd Annual Conference on Disability in Healthcare and Medicine
Stanford School of Medicine’s 2nd Annual Conference on Disability in Healthcare and Medicine
Apr 10 @ 8:00 am – 6:00 pm
Stanford School of Medicine's 2nd Annual Conference on Disability in Healthcare and Medicine

Date: April 10, 2021 (8 AM-6PM)

    • 8 AM-8:20 AM opening remarks Zainub and Pete
    • 8:20 AM-9:20 AM Talk 1 “I fought the law and no one won”
  • 10 minute Break
  • 9:30 AM-10:30 AM talk 2 students and doctors with disabilities panel
  • 20 minute break
    • 10:50 AM-11:50 AM Breakout
    • One hour lunch  (TBD)
    • 12:50 PM-1:50 PM Talk 3 the frontiers of disability research 
  • Lisa Meeks is moderating
  • Bonnie Swenor invited
    • 10 minute break
    • 2:00 PM-3:00 PM breakout 2
  • 10 minute break
  • 3:10 PM-4:10 PM talk 4 do-it-yourself disability advocacy (Poullos/Tolchin with students)
  • 4:10 PM-4:30 PM closing remarks
  • 4:30 PM-6 PM virtual happy hour

 

 

Jun
3
Thu
2021
IMMERS - Stanford Medical Mixed Reality Panel Discussion Series @ Zoom
IMMERS – Stanford Medical Mixed Reality Panel Discussion Series
Jun 3 @ 9:00 am – 10:30 am Zoom
IMMERS - Stanford Medical Mixed Reality Panel Discussion Series @ Zoom

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)

Jul
16
Fri
2021
Radiology-Wide Research Conference @ Zoom – Details can be found here: https://radresearch.stanford.edu
Radiology-Wide Research Conference
Jul 16 @ 12:00 pm – 1:00 pm Zoom – Details can be found here: https://radresearch.stanford.edu
Radiology-Wide Research Conference @ Zoom – Details can be found here: https://radresearch.stanford.edu

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

Aug
3
Tue
2021
2021 AIMI Symposium + BOLD-AIR Summit @ Virtual Livestream
2021 AIMI Symposium + BOLD-AIR Summit
Aug 3 @ 8:00 am – Aug 4 @ 3:00 pm Virtual Livestream
2021 AIMI Symposium + BOLD-AIR Summit @ Virtual Livestream

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.

 

REGISTER HERE

Sep
22
Wed
2021
IBIIS & AIMI Seminar: Seeing the Future from Images: ML-Based Models for Cancer Risk Assessment @ Zoom: https://stanford.zoom.us/j/99474772502?pwd=NEQrQUQ0MzdtRjFiYU42TCs2bFZsUT09
IBIIS & AIMI Seminar: Seeing the Future from Images: ML-Based Models for Cancer Risk Assessment
Sep 22 @ 11:00 am – 12:00 pm Zoom: https://stanford.zoom.us/j/99474772502?pwd=NEQrQUQ0MzdtRjFiYU42TCs2bFZsUT09

 

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.

Sep
27
Mon
2021
2021 IBIIS & AIMI Virtual Retreat
Sep 27 @ 1:00 pm – 4:30 pm https://ibiis.stanford.edu/events/retreat/2021Hybrid.html

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.

Oct
14
Thu
2021
Alone in the Ring - presented by SMAC and Stanford Medicine and the Muse
Alone in the Ring – presented by SMAC and Stanford Medicine and the Muse
Oct 14 @ 5:30 pm – 7:00 pm
Alone in the Ring - presented by SMAC and Stanford Medicine and the Muse

Alone in the Ring (a research-based theatre production about inclusive healthcare workplaces) is coming to campus during the Annual Stanford School of Medicine Diversity Week and National Disability Employment Awareness Month, SMAC and Stanford Medicine and the Muse hope to continue the discussion on how to spark and sustain change towards inclusive workspaces. Alone in the Ring is followed by a discussion between the team and audience members. During the presentation, audience members are encouraged to reflect: How inclusive is your workspace? How could you make it more accessible?

Register for this event