Tessa Cook, MD, PhD
Assistant Professor of Radiology
Perelman School of Medicine
University of Pennsylvania
Title: Deploying AI in the Clinical Radiology Workflow: Challenges, Opportunities, and Examples
Abstract: Although many radiology AI efforts are focused on pixel-based tasks, there is great potential for AI to impact radiology care delivery and workflow when applied to reports, EMR data, and workflow data. Radiology-pathology correlation, identification of follow-up recommendations, and report segmentation can be used to increase meaningful feedback to radiologists as well as to automate tasks that are currently manual and time-consuming. When deploying AI within the clinical workflow, there are many challenges that may slow down or otherwise affect the integration. Careful consideration of the way in which radiologists may expect to interact with AI results should be undertaken to meaningfully deploy radiology AI in a safe and effective way.
Please note this seminar is now cancelled and will be rescheduled for a future date. Please contact Ashley Williams (ashleylw@stanford.edu) with any questions or concerns. Thank you for your understanding!
CEDSS: “The First Cell and the Human Cost of going after Cancer’s last”
Chan Soon-Shiong Professor of Medicine
Director, Myelodysplastic Syndrome Center
Columbia University Medical Center
Please note this seminar is now cancelled and will be rescheduled for a future date. Please contact Ashley Williams (ashleylw@stanford.edu) with any questions or concerns. Thank you for your understanding!
IMAGinING THE FUTURE: “Journey Through Academia, Government and Industry: Lessons Learned”
Elias Zerhouni, M.D.
Professor Emeritus
John Hopkins University
Radiomics and Radio-Genomics: Opportunities for Precision Medicine
Zoom: https://stanford.zoom.us/j/99904033216?pwd=U2tTdUp0YWtneTNUb1E4V2x0OTFMQT09
Pallavi Tiwari, PhD
Assistant Professor of Biomedical Engineering
Associate Member, Case Comprehensive Cancer Center
Director of Brain Image Computing Laboratory
School of Medicine | Case Western Reserve University
Abstract:
In this talk, Dr. Tiwari will focus on her lab’s recent efforts in developing radiomic (extracting computerized sub-visual features from radiologic imaging), radiogenomic (identifying radiologic features associated with molecular phenotypes), and radiopathomic (radiologic features associated with pathologic phenotypes) techniques to capture insights into the underlying tumor biology as observed on non-invasive routine imaging. She will focus on clinical applications of this work for predicting disease outcome, recurrence, progression and response to therapy specifically in the context of brain tumors. She will also discuss current efforts in developing new radiomic features for post-treatment evaluation and predicting response to chemo-radiation treatment. Dr. Tiwari will conclude with a discussion on her lab’s findings in AI + experts, in the context of a clinically challenging problem of post-treatment response assessment on routine MRI scans.
Stanford Molecular Imaging Scholars (SMIS) Program
Quarterly Seminar
Andrew Groll, PhD
Mentor: Craig Levin, PhD
“Initial Experimental Images from a CZT Preclinical PET System”
Brian Lee, PhD
Mentors: Sam Gambhir, MD, PhD; Craig Levin, PhD
“Precision Health Toilet for Cancer Screening”
CEDSS: “Multicancer detection of early-stage cancers with simultaneous tissue localization using a plasma cfDNA-based targeted methylation assay”
Eric Fung, M.D., Ph.D.
Senior Medical Director
GRAIL, Inc.
Please see zoom details below:
Meeting URL: https://stanford.zoom.us/j/230531527
Dial: +1 650 724 9799 (US, Canada, Caribbean Toll) or +1 833 302 1536 (US, Canada, Caribbean Toll Free)
Meeting ID: 230 531 527
ABOUT
Dr. Eric Fung is Vice President, Clinical Development at GRAIL, where he leads several clinical development programs in support of the development of a blood-based multi-cancer detection test. Dr. Fung has previously held clinical development and R&D leadership roles at Affymetrix, Vermillion, Ciphergen, and Roche Molecular Diagnostics. Dr. Fung has led clinical trials leading to FDA clearance of multiple IVD products. Dr. Fung received his MD, PhD from the Johns Hopkins University School of Medicine.
Hosted by: Sanjiv Sam Gambhir, M.D., Ph.D.
Sponsored by the Canary Center & the Department of Radiology
Stanford University – School of Medicine
Stanford Molecular Imaging Scholars (SMIS) Program Quarterly Seminar
Zoom meeting: https://stanford.zoom.us/j/99117388314?pwd=R29OSjlTdUt0a3pLaG5Zc1BFNTJIUT09
Password: 922183
Guolan Lu, PhD
Mentor: Eben Rosenthal, MD; Garry Nolan, PhD
“Co-administered Antibody Improves the Penetration of Antibody-Dye Conjugates into Human Cancers: Implications for AntibodyDrug Conjugates”
Dianna Jeong, PhD
Mentors: Craig Levin, PhD; Shan Wang, PhD
“Novel Detection Approaches for Achieving Ultra-fast time resolution for PET”
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
Cancer Research UK, OHSU Knight Cancer Institute and the Canary Center at Stanford, present the Early Detection of Cancer Conference series. The annual Conference brings together experts in early detection from multiple disciplines to share ground breaking research and progress in the field.
The Conference is part of a long-term commitment to invest in early detection research, to understand the biology behind early stage cancers, find new detection and screening methods, and enhance uptake and accuracy of screening.
The 2020 conference will take place October 6-8 virtually.
Cancer Research UK, OHSU Knight Cancer Institute and the Canary Center at Stanford, have been closely monitoring developments relating to the coronavirus (COVID-19) outbreak and reviewing guidance from government bodies. After careful consideration, we have made the decision to convert the Early Detection of Cancer Conference 2020 to a virtual conference, instead of the scheduled in-person conference on October 6-8 in London, UK.
For more information visit the website: http://earlydetectionresearch.com/
CEDSS: “The Origins and Detection of Lethal Prostate Cancer”
Paul Boutros, Ph.D., M.B.A.
Director, Cancer Data Sciences
UCLA
Please see zoom details below:
Meeting URL: https://stanford.zoom.us/s/93515779500
Dial: +1 650 724 9799 or +1 833 302 1536
Meeting ID: 935 1577 9500
Meeting Passcode: 767148
ABOUT
Boutros earned his B.Sc. degree from the University of Waterloo in Chemistry in 2004, and his Ph.D. degree from the University of Toronto, Canada, in Medical Biophysics in 2008. At Toronto, he also earned an executive M.B.A. from the Rothman School of Management. In 2008, Boutros started his independent research career at the Ontario Institute for Cancer Research first as a fellow (2008–2010) and then as principal investigator (2010–2018). He moved to California to join the UCLA faculty in 2018.
Hosted by: Utkan Demirci, Ph.D.
Sponsored by the Canary Center & the Department of Radiology
Stanford University – School of Medicine