Send us a textDigiPath Digest #5 is ready as audio!We explore how AI and image datasets can accelerate medical education for both radiology and pathology. I review comparisons between the GPT-4 vision model and convolutional neural networks for neuropathological changes in the brain. We  explore how AI can potentially reduce healthcare costs, particularly in cancer risk discrimination. Additionally, there's a focus on AI applications in digital urine cytology for bladder cancer diagnosis. I also share personal updates, upcoming podcast guests, and my plans for utilizing YouTube content to create an educational course. The episode wraps up with a lively discussion on integrating AI in clinical workflows and prioritizing patient care.TIMESTAMPS:00:00 Introduction and Podcast Updates03:41 Guest Highlights and Personal Updates06:33 Digital Self-Learning in Radiology12:14 AI in Breast Cancer Risk Assessment18:36 Comparing GPT-4 Vision and CNN in Neuropathology21:58 Challenges in Lesion Identification22:59 Few-Shot Learning in Neuropathology24:42 AI in Bladder Cancer Diagnosis29:48 Innovations in Digital Pathology38:48 AI-Powered Clinical Workflows44:42 Conclusion and Future DirectionsTODAY'S ABSTRACTS & RESOURCES:Improving the diagnostic performance of inexperienced readers for thyroid nodules through digital self-learning and artificial intelligence assistanceU.S. payer budget impact of using an AI-augmented cancer risk discrimination digital histopathology platform to identify high-risk of recurrence in women with early-stage invasive breast cancerEvaluating the efficacy of few-shot learning for GPT-4Vision in neurodegenerative disease histopathology: A comparative analysis with convolutional neural network modelEvaluating artificial intelligence-enhanced digital urine cytology for bladder cancer diagnosisSupport the showGet the "Digital Pathology 101" FREE E-book and join us!

Ver todos los episodios