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This first-of-its-kind virtual environment allows healthcare professionals to experience and assess healthcare AI technologies in a data-rich, interactive setting. The Healthcare AI Challenge levels the playing field by comparing AI performance in a standardized manner. Help us advance the future of AI in healthcare!

Speaker: Andrey Fedorov, PhD The Imaging Data Commons - Data Tools Compute to Power Your AI Explorations

Speaker: William Hsu, PhD Presentation: Opportunities and Challenges of Using Multimodal Data to Detect and Diagnose Cancers Earlier

AI4C Lecture Series: AI: Are We Heading in the Right Direction?

AI4C Lecture Series: Practical Considerations for Addressing Fairness and Bias Issues in Radiology

Dr. Nina Kottler, MD, MS presents the Artificial Intelligence for Clinicians Lecture Series: "The Tech Enabled Future of Radiology - Bridging the Gap to a New Era" The field of radiology stands on the brink of transformation, propelled by rapidly evolving technological advancements. In this session, Dr. Kottler explores the dynamic future of radiology as we integrate AI and other innovative tec...

In this presentation, Dr. Matthew Brown of UCLA will discuss how deep neural networks detect patterns in data and have shown versatility and strong performance in many computer vision applications. However, they are susceptible to obvious mistakes that violate common sense concepts and are limited in their ability to use knowledge to guide their decision making. While overall performance metric...

In this presentation, Dr. Michael Rosenthal of Brigham and Women's Hospital discusses the role of AI in diagnosing pancreatic cancer. Pancreatic cancer is the third leading cause of cancer death in the United States, due in part to the advanced state of disease in 85% of newly diagnosed patients. Early detection can markedly improve survival but has been limited to high-risk families. Artificia...

The gap between the tens of thousands of AI algorithms that have been developed and their actual implementation in radiology, nuclear medicine and cardiology is continuing to widen as more sophisticated and innovative applications emerge that are currently not in the hands of radiologists or clinicians. The purpose of this presentation is to lead a discussion of the current status of AI in clin...

Speaker: Omar Arnaout, MD Title: AI in Neurosurgery In this talk, Dr. Arnaout will discuss various applications of AI/ML in the daily practice of neurosurgery and explore avenues for future exploration. Dr. Omar Arnaout has a particular interest and sub-specialized training in treating patients with brain tumors, including those with glioma, metastatic disease and skull base tumors including me...

Speaker: Judy Wawira Gichoya, MD, MS Talk Title: Hidden in Plain Sight: An Update to the Reading Race Project There is an old saying, “a picture is worth more than a thousand words”. We increasingly observe this phenomenon where AI models are increasingly shown to outperform radiologists to detect features like gender, race, social determinants of health and health care costs. This ability has ...

Dr. Synho Do presents "Explainable AI for Transparent and Real-world Performance Monitoring" at the AI4C Lecture Series. October, 2022

Dr. Hadi Shafiee, Ph.D. presents the Artificial Intelligence for Clinicians Lecture Series: "AI Engineered Smartphone-Enabled Diagnostics and Frameworks with Applications in Infectious Diseases and Infertility".

Dr. Matthew Li presents the Artificial Intelligence for Clinicians Lecture Series: "Radiology AI During the COVID-19 Pandemic: A Personal Journey and Lessons Learned." Dr. Li is a diagnostic radiology fellow and former chief resident in the department of radiology at Massachusetts General Hospital and Harvard Medical School. Numerous imaging-based artificial intelligence (AI) models were develo...

AI4C Lecture Series: An Alternative to the Black Box: Strategy Learning

AI4C Lecture Series: AI in Radiology: Opportunities and Challenges of Real Word Deployment

AI4C Lecture Series: Deep Learning in Radiology - Emerging Trends and New Research

AI4C Lecture Series: Challenges and Opportunities for AI in Abdominal Radiology

AI4C Lecture Series: Global Regulation of AI - What You Need to Know

AI4C Lecture Series: Opportunities and Challenges in the Application of AI to Radiology and Medicine

AI4C Lecture Series: Attribution Theory and Achieving AI Automation in Radiology