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Machine Learning in Medical Imaging: A Regulatory Success Story
Manage episode 451384881 series 3617575
Innhold levert av Nirdosh Jagota. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Nirdosh Jagota eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.
In this episode of AI Revolution in Healthcare: A Regulatory Perspective, Dr. Nirdosh Jagota explores the transformative role of machine learning in medical imaging and its regulatory journey. He highlights a Swedish study where AI-assisted breast cancer screening improved detection rates by 4% compared to traditional methods.
Dr. Jagota examines three key aspects of AI in imaging: regulatory frameworks, performance validation, and integration into clinical workflows. He discusses the FDA’s approach to AI imaging devices, including concepts like predetermined change control plans (PCCP) to accommodate AI's ability to learn over time.
Listeners will gain insights into the validation requirements for AI imaging systems, including analytical and clinical validity, and the importance of transparency in AI decision-making. The episode also covers the growing trend of real-world performance monitoring.
Join Dr. Jagota as he discusses how regulatory frameworks are enabling AI to safely innovate medical imaging, paving the way for advancements in other healthcare sectors.
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