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DTSTART;TZID=America/New_York:20260327T120000
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UID:10003580-1774612800-1774616400@events.med.miami.edu
SUMMARY:The Future of Health Data Innovation: Drug Discovery using Systems Biology and Mechanistic AI [FREE CME]
DESCRIPTION:📅 Friday March 27th\, 2026\n🕐 12:00 PM – 1:00 PM\n📍 Virtual Event (Zoom Webinar)\nRegister Now\n\n \n\nThe Future of Health Data Innovation \n“Drug Discovery using Systems Biology and Mechanistic AI“ \n1.0 AMA PRA Category 1 Credit™\n\n \n\n \n\n \n\n \n\nFeatured Speaker \nDr. Sriram Chandrasekaran PhD\nAssociate Professor\, Biomedical Engineering \nAssociate Chair for Research in Biomedical Engineering \nLeader of the Systems Biology & Drug Discovery Lab \nUniversity of Michigan \n\n\n \n\nAbout Dr. Chandrasekaran\nSriram Chandrasekaran is an Associate Professor and Associate Chair of Research in Biomedical Engineering at the University of Michigan-Ann Arbor. He leads the Systems Biology & Drug Discovery lab. He received his PhD in Biophysics from the University of Illinois at Urbana-Champaign and later worked as a Harvard Junior Fellow at Harvard University and MIT.  His lab has developed more than 15 systems-biology methods for drug discovery and bioengineering. A key focus of his lab is developing mechanistic AI methods that integrate engineering models and machine learning. He teaches a course called AI in BME that introduces students to AI algorithms and their applications in biomedical engineering. He is the recipient of several awards\, including the MIT Technology Review’s Top Innovators Under 35 (TR35) award and the EBS Teaching Award. \n\n \n\nLearning Objectives\nAt the conclusion of this activity\, participants will be able to: \n\n\nIllustrate the importance of combination therapy\, specifically in the context of overcoming drug resistance in cancer and infectious diseases.\n\n\nExplain the need for Systems Biology and AI in Drug Discovery\, transitioning from generalized treatments to personalized approaches\n\nIdentify critical factors used by AI tools to predict the efficacy of a drug regimen: Properties of the drugs\, the pathogen or tumor\, and the disease environment.\n\n\n \n\nVenue\n\nVirtual Event \nJoin via Zoom Webinar (registration required) \nRegister Now \n\n\n \n\nAccreditation & Credits\n\n\nAccreditation \nThe University of Miami Leonard M. Miller School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.                                                                                                                                                                                                                                                                                                                                             \n\n\nCredit Designation \nThe University of Miami Leonard M. Miller School of Medicine designates this live activity for a maximum of 1 AMA PRA Category 1 Credit™. Physicians should claim only the credit commensurate with the extent of their participation in the activity. \n\n\n\n \n\nDisclosures\n\nMitigation of Relevant Financial Relationships \nThe University of Miami adheres to the ACCME’s Standards for Integrity and Independence in Accredited Continuing Education. Any individuals in a position to control the content of a CE activity\, including faculty\, planners\, reviewers or others are required to disclose all relevant financial relationships with ineligible entities (commercial interests). All relevant conflicts of interest have been mitigated prior to the commencement of the activity. \n\n\n \n\nContact Information\n\nOrganizer \nAlex Gonzalez\n786-708-7312 · axg6653@miami.edu \n\n\n \n\nEvent Category\nInformatics and Health Data Science · Dept. of Medicine · Public Health Sciences \n\n \n\nThe Future of Health Data Innovation \n“Drug Discovery using Systems Biology and Mechanistic AI“ \nFriday\, March 27th\, 2026 · 12:00 PM – 1:00 PM · Virtual Event \nRegister Now
URL:https://events.med.miami.edu/event/fhdi-march-2026/
CATEGORIES:Alumni,Dept. of Medicine,Informatics and Health Data Science,Public Health Sciences,The MIL Lab,TSCS
ORGANIZER;CN="Alex Gonzalez":MAILTO:axg6653@miami.edu
LOCATION:https://events.med.miami.edu/event/fhdi-march-2026/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260226T120000
DTEND;TZID=America/New_York:20260226T130000
DTSTAMP:20260213T172315Z
CREATED:20260213T172104Z
LAST-MODIFIED:20260213T172315Z
UID:10003556-1772107200-1772110800@events.med.miami.edu
SUMMARY:The Future of Health Data Innovation: Process of Training Clinicians on the Use of Artificial Intelligence in Healthcare and Algorithmic Bias [CME eligible]
DESCRIPTION:📅 Thursday\, February 26th\, 2026\n🕐 12:00 PM – 1:00 PM\n📍 Virtual Event (Zoom Webinar)\nRegister Now\n\n \n\nThe Future of Health Data Innovation \n“Process of Training Clinicians on the Use of Artificial Intelligence in Healthcare and Algorithmic Bias” \n1.0 AMA PRA Category 1 Credit™\n\n \n\n \n\nDr. Benjamin Collins MD\, MA\, MS \n\n \n\nFeatured Speaker \nDr Benjamin Collins MD\, MA\, MS\nAssistant Professor Department of Medicine \nAssistant Professor Department of Biomedical Informatics \nVanderbilt University \n\n\n \n\nAbout Dr. Collins\nDr. Benjamin Collins is an Assistant Professor of Clinical Medicine in the Division of General Internal Medicine and Public Health with a secondary appointment in the Department of Biomedical Informatics at Vanderbilt University Medical Center (VUMC). He completed Internal Medicine Residency at Temple University Hospital in Philadelphia\, PA and earned an MA degree in Urban Bioethics during residency with a thesis on\, “A Theory of Sociotechnical Justice in Healthcare.” \nHe completed a clinical informatics fellowship at Oregon Health & Science University in Portland\, OR along with an MS degree in biomedical informatics with a capstone project on developing an online training module for clinicians in healthcare. This work received the 2022 American Medical Informatics Association Academic Forum Best Paper Award. He also completed a research fellowship at VUMC on ethical\, legal\, and social issues of AI in healthcare.  At VUMC\, he currently practices clinically as a hospitalist and works on research around ethics and equity in the context of clinical reasoning with AI in healthcare. \n\n \n\nLearning Objectives\nAt the conclusion of this activity\, participants will be able to: \n\n\nExplain the importance of training clinicians on the use of artificial intelligence in healthcare and potential for algorithmic bias. \n\n\nAnalyze scientific literature to identify important content for clinicians to learn related to artificial intelligence in healthcare and algorithmic bias. \n\n\nPlan training for clinicians on topics of emerging importance related to the use of artificial intelligence in healthcare. \n\n\n\n \n\nVenue\n\nVirtual Event \nJoin via Zoom Webinar (registration required) \nRegister Now \n\n\n \n\nAccreditation & Credits\n\n\nAccreditation \nThe University of Miami Leonard M. Miller School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. \n\n\nCredit Designation \nThe University of Miami Leonard M. Miller School of Medicine designates this live activity for a maximum of 1 AMA PRA Category 1 Credit™. Physicians should claim only the credit commensurate with the extent of their participation in the activity. \n\n\n\n \n\nDisclosures\n\nMitigation of Relevant Financial Relationships \nThe University of Miami adheres to the ACCME’s Standards for Integrity and Independence in Accredited Continuing Education. Any individuals in a position to control the content of a CE activity\, including faculty\, planners\, reviewers or others are required to disclose all relevant financial relationships with ineligible entities (commercial interests). All relevant conflicts of interest have been mitigated prior to the commencement of the activity. \n\n\n \n\nContact Information\n\nOrganizer \nAlex Gonzalez\n786-708-7312 · axg6653@miami.edu \n\n\n \n\nEvent Category\nInformatics and Health Data Science · Dept. of Medicine · Public Health Sciences \n\n \n\nThe Future of Health Data Innovation \n“Process of Training Clinicians on the Use of Artificial Intelligence in Healthcare and Algorithmic Bias” \nThursday\, February 26th\, 2026 · 12:00 PM – 1:00 PM · Virtual Event \nRegister Now
URL:https://events.med.miami.edu/event/the-future-of-health-data-innovation-process-of-training-clinicians-on-the-use-of-artificial-intelligence-in-healthcare-and-algorithmic-bias-cme-eligible/
CATEGORIES:Alumni,Dept. of Medicine,Informatics and Health Data Science,Public Health Sciences,The MIL Lab,TSCS
ORGANIZER;CN="Alex Gonzalez":MAILTO:axg6653@miami.edu
LOCATION:https://events.med.miami.edu/event/the-future-of-health-data-innovation-process-of-training-clinicians-on-the-use-of-artificial-intelligence-in-healthcare-and-algorithmic-bias-cme-eligible/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260129T120000
DTEND;TZID=America/New_York:20260129T130000
DTSTAMP:20260213T170833Z
CREATED:20260213T154418Z
LAST-MODIFIED:20260213T170833Z
UID:10003506-1769688000-1769691600@events.med.miami.edu
SUMMARY:The Future of Health Data Innovation: Process of Training Clinicians on the Use of Artificial Intelligence in Healthcare and Algorithmic Bias [CME eligible]
DESCRIPTION:📅 Thursday\, February 26th\, 2026\n🕐 12:00 PM – 1:00 PM\n📍 Virtual Event (Zoom Webinar)\nRegister Now\n\n \n\nThe Future of Health Data Innovation \n“Process of Training Clinicians on the Use of Artificial Intelligence in Healthcare and Algorithmic Bias” \n1.0 AMA PRA Category 1 Credit™\n\n \n\n \n\nDr. Benjamin Collins MD\, MA\, MS \n\n \n\nFeatured Speaker \nDr Benjamin Collins MD\, MA\, MS\nAssistant Professor Department of Medicine \nAssistant Professor Department of Biomedical Informatics \nVanderbilt University \n\n\n \n\nAbout Dr. Collins\nDr. Benjamin Collins is an Assistant Professor of Clinical Medicine in the Division of General Internal Medicine and Public Health with a secondary appointment in the Department of Biomedical Informatics at Vanderbilt University Medical Center (VUMC). He completed Internal Medicine Residency at Temple University Hospital in Philadelphia\, PA and earned an MA degree in Urban Bioethics during residency with a thesis on\, “A Theory of Sociotechnical Justice in Healthcare.” \nHe completed a clinical informatics fellowship at Oregon Health & Science University in Portland\, OR along with an MS degree in biomedical informatics with a capstone project on developing an online training module for clinicians in healthcare. This work received the 2022 American Medical Informatics Association Academic Forum Best Paper Award. He also completed a research fellowship at VUMC on ethical\, legal\, and social issues of AI in healthcare.  At VUMC\, he currently practices clinically as a hospitalist and works on research around ethics and equity in the context of clinical reasoning with AI in healthcare. \n\n \n\nLearning Objectives\nAt the conclusion of this activity\, participants will be able to: \n\n\nExplain the importance of training clinicians on the use of artificial intelligence in healthcare and potential for algorithmic bias. \n\n\nAnalyze scientific literature to identify important content for clinicians to learn related to artificial intelligence in healthcare and algorithmic bias. \n\n\nPlan training for clinicians on topics of emerging importance related to the use of artificial intelligence in healthcare. \n\n\n\n \n\nVenue\n\nVirtual Event \nJoin via Zoom Webinar (registration required) \nRegister Now \n\n\n \n\nAccreditation & Credits\n\n\nAccreditation \nThe University of Miami Leonard M. Miller School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. \n\n\nCredit Designation \nThe University of Miami Leonard M. Miller School of Medicine designates this live activity for a maximum of 1 AMA PRA Category 1 Credit™. Physicians should claim only the credit commensurate with the extent of their participation in the activity. \n\n\n\n \n\nDisclosures\n\nMitigation of Relevant Financial Relationships \nThe University of Miami adheres to the ACCME’s Standards for Integrity and Independence in Accredited Continuing Education. Any individuals in a position to control the content of a CE activity\, including faculty\, planners\, reviewers or others are required to disclose all relevant financial relationships with ineligible entities (commercial interests). All relevant conflicts of interest have been mitigated prior to the commencement of the activity. \n\n\n \n\nContact Information\n\nOrganizer \nAlex Gonzalez\n786-708-7312 · axg6653@miami.edu \n\n\n \n\nEvent Category\nInformatics and Health Data Science · Dept. of Medicine · Public Health Sciences \n\n \n\nThe Future of Health Data Innovation \n“Process of Training Clinicians on the Use of Artificial Intelligence in Healthcare and Algorithmic Bias” \nThursday\, February 26th\, 2026 · 12:00 PM – 1:00 PM · Virtual Event \nRegister Now
URL:https://events.med.miami.edu/event/fhdi2026-algorithmic-bias/
CATEGORIES:Alumni,Dept. of Medicine,Informatics and Health Data Science,Public Health Sciences,The MIL Lab,TSCS
ORGANIZER;CN="Alex Gonzalez":MAILTO:axg6653@miami.edu
LOCATION:https://events.med.miami.edu/event/fhdi2026-algorithmic-bias/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260129T120000
DTEND;TZID=America/New_York:20260129T130000
DTSTAMP:20260114T163821Z
CREATED:20260114T151112Z
LAST-MODIFIED:20260114T163821Z
UID:10003460-1769688000-1769691600@events.med.miami.edu
SUMMARY:The Future of Health Data Innovation: Accelerating Systematic Reviews: Using AI-Assisted Python Coding for Literature Screening [CME eligible]
DESCRIPTION:📅 Thursday\, January 29\, 2026\n    \n\n        🕐 12:00 PM – 1:00 PM\n    \n\n        📍 Virtual Event (Zoom Webinar)\n    \n\n        Register Now\n    \n\n \n\nThe Future of Health Data Innovation \n“Accelerating Systematic Reviews: Using AI-Assisted Python Coding for Literature Screening” \n\n        1.0 AMA PRA Category 1 Credit™\n    \n\n \n\n     \n\n        \n    \n     \n\nFeatured Speaker \nLina Shehadeh\, Ph.D.\nProfessor of Medicine\, Division of Cardiology \nUniversity of Miami Miller School of Medicine \nResearch Health Scientist\, Miami VA Medical Center \n \n\n \n\nAbout Dr. Shehadeh\nDr. Lina Shehadeh is a Professor of Medicine in the Division of Cardiology at the University of Miami Miller School of Medicine and Research Health Scientist at the Miami VA Medical Center. Her NIH-\, AHA-\, and VA-funded laboratory investigates the role of metabolic dysfunction in Heart Failure with Preserved Ejection Fraction (HFpEF)\, and endothelial dysfunction in Long COVID. \nDr. Shehadeh’s expertise in computational biology\, data mining\, and machine learning enables her to leverage large genomic datasets to identify therapeutic targets. She is active in (bio)medical education research with a focus on integrating AI tools into research workflows\, and recently published a methods paper in the American Journal of Physiology-Heart and Circulatory Physiology on using AI-assisted Python coding to accelerate systematic review screening. \n\n \n\nLearning Objectives\nAt the conclusion of this activity\, participants will be able to: \n\n\nDescribe how AI-assisted Python coding can be applied to screen hundreds to thousands of abstracts for systematic literature reviews \n \n\nIdentify the key steps in implementing a rule-based automation protocol for efficient and reproducible literature screening \n \n\nEvaluate the advantages and limitations of AI-assisted screening compared to traditional manual approaches \n \n \n\n \n\nVenue\n\nVirtual Event \nJoin via Zoom Webinar (registration required) \n        Register Now\n    \n\n \n\nAccreditation & Credits\n\n\nAccreditation \nThe University of Miami Leonard M. Miller School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. \n \n\nCredit Designation \nThe University of Miami Leonard M. Miller School of Medicine designates this live activity for a maximum of 1 AMA PRA Category 1 Credit™. Physicians should claim only the credit commensurate with the extent of their participation in the activity. \n \n \n\n \n\nDisclosures\n\nMitigation of Relevant Financial Relationships \nThe University of Miami adheres to the ACCME’s Standards for Integrity and Independence in Accredited Continuing Education. Any individuals in a position to control the content of a CE activity\, including faculty\, planners\, reviewers or others are required to disclose all relevant financial relationships with ineligible entities (commercial interests). All relevant conflicts of interest have been mitigated prior to the commencement of the activity. \n \n\n \n\nContact Information\n\nOrganizer \nAlex Gonzalez786-708-7312 · axg6653@miami.edu \n \n\n \n\nEvent Category\nInformatics and Health Data Science · Dept. of Medicine · Public Health Sciences \n\n \n\nThe Future of Health Data Innovation \n“Accelerating Systematic Reviews: Using AI-Assisted Python Coding for Literature Screening” \nThursday\, January 29\, 2026 · 12:00 PM – 1:00 PM · Virtual Event \n    Register Now
URL:https://events.med.miami.edu/event/fhdi-accelerating-systematic-reviews/
CATEGORIES:Alumni,Dept. of Medicine,Informatics and Health Data Science,Public Health Sciences,The MIL Lab,TSCS
ORGANIZER;CN="Alex Gonzalez":MAILTO:axg6653@miami.edu
LOCATION:https://events.med.miami.edu/event/fhdi-accelerating-systematic-reviews/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251204T110000
DTEND;TZID=America/New_York:20251204T120000
DTSTAMP:20251124T224943Z
CREATED:20251103T003005Z
LAST-MODIFIED:20251124T224943Z
UID:10003328-1764846000-1764849600@events.med.miami.edu
SUMMARY:The Future of Health Data Innovation: A Privacy-Centric and Federated Approach to Machine Learning for the Collection and Sharing of Patient-Reported Outcomes Data in Genomic Medicine Research [CME eligible]
DESCRIPTION:Featuring Rachele Hendricks-Sturrup DHSc\, MSc\, MA\n \nDr. Rachele Hendricks-Sturrup is the Research Director of Real-World Evidence (RWE) at the Duke-Margolis Institute for Health Policy in Washington\, DC\, strategically leading and managing the Institute’s RWE Collaborative and RWE policy research portfolio and education. As an engagement expert\, biomedical researcher\, bioethicist\, and policy practitioner with over 18 years of experience\, her work centers on addressing implementation\, regulatory\, and ethical\, legal\, and social implications (ELSI) at the intersection of health policy and innovation. She presently partners with Duke University faculty\, scholars\, students\, and external practicing experts to advance the Institute’s biomedical innovation work. \n\nObjectives\n\nExplain the importance of collecting patient-reported outcomes (PROs) data in genomic medicine research.\nInterpret clinical use cases and PRO data collection tools that have been used in genomic medicine research and care settings.\nIllustrate a patient-facing\, privacy-preserving\, and machine learning-based mechanism that could be used to facilitate the collection and sharing of sensitive PRO data to support genomic medicine research.\n\nAccreditation\nThe University of Miami Leonard M. Miller School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. \nCredit Designation\nThe University of Miami Leonard M. Miller School of Medicine designates this live activity for a maximum of 1  AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity. \nMitigation of Relevant Financial Relationships\nThe University of Miami adheres to the ACCME’s Standards for Integrity and Independence in Accredited Continuing Education. Any individuals in a position to control the content of a CE activity\, including faculty\, planners\, reviewers or others are required to disclose all relevant financial relationships with ineligible entities (commercial interests). All relevant conflicts of interest have been mitigated prior to the commencement of the activity.
URL:https://events.med.miami.edu/event/privacy-centric-and-federated-approach/
CATEGORIES:Alumni,Dept. of Medicine,Informatics and Health Data Science,Public Health Sciences,The MIL Lab,TSCS
ORGANIZER;CN="Alex Gonzalez":MAILTO:axg6653@miami.edu
LOCATION:https://events.med.miami.edu/event/privacy-centric-and-federated-approach/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251120T110000
DTEND;TZID=America/New_York:20251120T120000
DTSTAMP:20251029T162715Z
CREATED:20251019T201318Z
LAST-MODIFIED:20251029T162715Z
UID:10003309-1763636400-1763640000@events.med.miami.edu
SUMMARY:The Future of Health Data Innovation: Artificial Intelligence for Rural US Healthcare [CME eligible]
DESCRIPTION:Featuring Dr. Katherine Brown\n \nDr. Katherine (Katie) Brown a biomedical informaticist working at the intersection of state-of-the-art artificial intelligence and machine learning (AI/ML)\, informatics for rural healthcare\, and optimizing AI/ML systems for human collaboration. Her overarching goal as a researcher is to develop and evaluate AI/ML systems that promote equity in healthcare access and patient outcomes while maintaining and enhancing performance\, robustness\, and reliability.  Currently\, she is a T15 Postdoctoral Research Fellow in the Department of Biomedical Informatics at Vanderbilt University Medical Center\, and she received her B.S. in Computer Science in May 2018\, her M.S. in Computer Science in May 2021\, and her PhD in Engineering (Computer Science) in August 2023\, all from Tennessee Technological University. She has served on the Student Editorial Board of the Journal of the American Medical Informatics Association (JAMIA) in the 2022-2024 cohort and is currently serving on the Editorial Board of JAMIA in the 2025-2027 cohort.  \n\nObjectives\n\nQuantify current state of AI/ML research and development for healthcare in the rural US\nIllustrate challenges faced when implementing AI/ML methods for rural populations\nEvaluate the efficacy of various methods — including synthetic data generation\, federated learning\, and foundation models — in mitigating concerns about model development\n\n\nAccreditation\nThe University of Miami Leonard M. Miller School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. \nCredit Designation\nThe University of Miami Leonard M. Miller School of Medicine designates this live activity for a maximum of 1  AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity. \nMitigation of Relevant Financial Relationships\nThe University of Miami adheres to the ACCME’s Standards for Integrity and Independence in Accredited Continuing Education. Any individuals in a position to control the content of a CE activity\, including faculty\, planners\, reviewers or others are required to disclose all relevant financial relationships with ineligible entities (commercial interests). All relevant conflicts of interest have been mitigated prior to the commencement of the activity.
URL:https://events.med.miami.edu/event/rural-us-healthcare/
CATEGORIES:Alumni,Dept. of Medicine,Informatics and Health Data Science,Public Health Sciences,The MIL Lab,TSCS
ORGANIZER;CN="Alex Gonzalez":MAILTO:axg6653@miami.edu
LOCATION:https://events.med.miami.edu/event/rural-us-healthcare/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251023T110000
DTEND;TZID=America/New_York:20251023T120000
DTSTAMP:20251021T205404Z
CREATED:20251003T131855Z
LAST-MODIFIED:20251021T205404Z
UID:10003236-1761217200-1761220800@events.med.miami.edu
SUMMARY:The Future of Health Data Innovation - How AI is Revolutionizing Radiology
DESCRIPTION:Featuring Dr. Alexander Brost\nPlease join the Department of Informatics and Health Data Science and the Media and Innovation Lab in welcoming Dr. Alexander Brost for a cutting-edge presentation on how AI is revolutionizing the radiology. Dr. Brost is Head of Clinical Innovation & Concepts at Siemens Healthineers\, Digital & Automation\, where he leads strategic initiatives in AI and clinical innovation. With over 15 years of experience spanning research\, product management\, and innovation leadership\, Dr. Brost has played a pivotal role in translating cutting-edge technologies into impactful healthcare solutions. Dr. Brost holds a doctoral degree from Friedrich-Alexander-Universität Erlangen-Nürnberg\, with research experience at Stanford University and Siemens Corporate Technology. His academic work focused on image processing\, earning him the Advancement Award from the German Society for Biomedical Engineering.  \nObjectives\nDemonstrate insights into technical aspects and highlight the importance of close collaboration/interaction between the fields involved: radiologist\, computer scientists\, data scientist\, etc. \nDate & Time\nOctober 23rd\, 2025 | 11 AM – 12 PM \nRegister Here
URL:https://events.med.miami.edu/event/how-ai-is-revolutionizing-radiology/
CATEGORIES:Informatics and Health Data Science
ORGANIZER;CN="Alex Gonzalez":MAILTO:axg6653@miami.edu
LOCATION:https://events.med.miami.edu/event/how-ai-is-revolutionizing-radiology/
END:VEVENT
END:VCALENDAR