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Machine Learning in Medical Imaging: A Regulatory Success Story
Manage episode 451384881 series 3617575
Вміст надано Nirdosh Jagota. Весь вміст подкастів, включаючи епізоди, графіку та описи подкастів, завантажується та надається безпосередньо компанією Nirdosh Jagota або його партнером по платформі подкастів. Якщо ви вважаєте, що хтось використовує ваш захищений авторським правом твір без вашого дозволу, ви можете виконати процедуру, описану тут https://uk.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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