Thursday MIPS Roundtable: Meet our MIPS Instructors
MIPS Roundtables are every other Thursday from 1:30-2:30pm showcasing various topics and are open to all interested. Note we will take a break through late July and August.
1:30-2:00 PM | Dr. Ahmed El Kaffas, Ph.D.
Translational Ultrasound for Tissue Characterization and Stimulation
Instructor, Radiology
Stanford University
2:00-2:30 PM | Dr. Brett Fite, Ph.D.
Combining Focal and Immunotherapies
Instructor, Radiology
Stanford University
Please note Zoom information does change week to week.
7/9 Webinar URL: https://stanford.zoom.us/j/91909413178
Dial: +1 650 724 9799 or +1 833 302 1536
Webinar ID: 919 0941 3178
Password: 572746
Thursday MIPS Roundtable: Meet our MIPS Instructors
MIPS Roundtables are Thursdays from 1:30-2:30pm showcasing various topics and are open to all interested. Note this will be our last summer Roundtable and we will take a break through late July and August.
1:30-2:00 PM | Dr. Josquin Foiret, Ph.D.
High throughput ultrasound imaging for improved diagnosis
Instructor, Radiology
Stanford University
2:00-2:30 PM | Dr. Jinghang Xie, Ph.D.
TESLA probes for imaging T cell-mediated cytotoxic response to immunotherapy
Instructor, Radiology
Stanford University
Please note Zoom information does change week to week.
7/16 Webinar URL: https://stanford.zoom.us/j/94952044130
Dial: +1 650 724 9799 or +1 833 302 1536
Webinar ID: 949 5204 4130
Password: 963699
Dear WMIS trainees, colleagues and friends,
We welcome you to join our upcoming virtual WMIS – Stanford Diversity conference on September 9-11, 2020. We are coming together to reinforce our commitment to diversity and to provide a forum for our team members to engage in meaningful discussions. The conference will provide keynote lectures, scientific presentations and educational lectures from leaders and pioneers in the field, who will discuss important topics related to racial justice, women in STEM and Global Health. We are also offering breakout sessions whereby carefully selected individuals will facilitate a discussion about how to implement more supportive and inclusive practices into our daily professional and personal life. The breakout sessions are designed to enable active involvement of smaller groups where people feel safe to discuss current challenges in the STEM field and actionable solutions.
This conference is free of charge and will provide 9.5 CME credits. Abstracts of all conference presentations and a summary of discussion points and insights provided by all conference participants will be published in Molecular Imaging & Biology. The organizing committee will provide 10 trainee prizes in the form of free WMIS memberships to conference attendants for the 2021 WMIC in Miami.
Website: https://www.wmislive.org
Judy Gichoya, MD
Assistant Professor
Emory University School of Medicine
Measuring Learning Gains in Man-Machine Assemblage When Augmenting Radiology Work with Artificial Intelligence
Abstract
The work setting of the future presents an opportunity for human-technology partnerships, where a harmonious connection between human-technology produces unprecedented productivity gains. A conundrum at this human-technology frontier remains – will humans be augmented by technology or will technology be augmented by humans? We present our work on overcoming the conundrum of human and machine as separate entities and instead, treats them as an assemblage. As groundwork for the harmonious human-technology connection, this assemblage needs to learn to fit synergistically. This learning is called assemblage learning and it will be important for Artificial Intelligence (AI) applications in health care, where diagnostic and treatment decisions augmented by AI will have a direct and significant impact on patient care and outcomes. We describe how learning can be shared between assemblages, such that collective swarms of connected assemblages can be created. Our work is to demonstrate a symbiotic learning assemblage, such that envisioned productivity gains from AI can be achieved without loss of human jobs.
Specifically, we are evaluating the following research questions: Q1: How to develop assemblages, such that human-technology partnerships produce a “good fit” for visually based cognition-oriented tasks in radiology? Q2: What level of training should pre-exist in the individual human (radiologist) and independent machine learning model for human-technology partnerships to thrive? Q3: Which aspects and to what extent does an assemblage learning approach lead to reduced errors, improved accuracy, faster turn-around times, reduced fatigue, improved self-efficacy, and resilience?
Zoom: https://stanford.zoom.us/j/93580829522?pwd=ZVAxTCtEdkEzMWxjSEQwdlp0eThlUT09
Join us for the 3rd Annual Diversity and Inclusion Forum on Friday, October 9, 2020 on Zoom! This virtual event will highlight innovative workshops developed by our residents and fellows with their educational mentors who have participated in the 2019-2020 cohort of the Leadership Education in Advancing Diversity Program.
The event will be an enriching opportunity for all faculty, residents, fellows, postdocs, students, staff, and community members to learn tools and strategies to enable them to become effective change agents for diversity, equity, and inclusion in medical education.
All are welcome to participate and we look forward to seeing you on Friday, October 9!
Register here:
https://mailchi.mp/046c21726371/diversityforum2020-1632872?e=4a913cab2d
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
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.
Radiology Department-Wide Research Meeting
• Curt Langlotz, MD, PhD: Overview of the AIMI Center
• Brian Hargreaves, PhD: Research Details from Town Hall, Q&A, and COVID19 Updates
Location: Zoom – Details can be found here: https://radresearch.stanford.edu
Meetings will be the 3rd Friday of each month.
Hosted by: Brian Hargreaves, PhD
Sponsored by: the the Department of Radiology
Radiology Department-Wide Research Meeting
Location: Zoom – Details can be found here: https://radresearch.stanford.edu
Meetings will be the 3rd Friday of each month.
February 19 Speakers:
Bruce Daniel, MD – Center Overview: IMMERS
Jennifer McNab, PhD – Encoding and Decoding Diffusion MRI
Hosted by: Brian Hargreaves, PhD
Sponsored by: the the Department of Radiology
Radiology Department-Wide Research Meeting
• Dominik Fleischmann, MD: 3DQ Lab Overview
• Tom Soh, PhD: Research Updates
Location: Zoom – Details can be found here: https://radresearch.stanford.edu
Meetings will be the 3rd Friday of each month.
Hosted by: Brian Hargreaves, PhD
Sponsored by: the the Department of Radiology