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DigiPath 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 Updates
03:41 Guest Highlights and Personal Updates
06:33 Digital Self-Learning in Radiology
12:14 AI in Breast Cancer Risk Assessment
18:36 Comparing GPT-4 Vision and CNN in Neuropathology
21:58 Challenges in Lesion Identification
22:59 Few-Shot Learning in Neuropathology
24:42 AI in Bladder Cancer Diagnosis
29:48 Innovations in Digital Pathology
38:48 AI-Powered Clinical Workflows
44:42 Conclusion and Future Directions
TODAY'S ABSTRACTS & RESOURCES:
Improving the diagnostic performance of inexperienced readers for thyroid nodules through digital self-learning and artificial intelligence assistance)
U.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 cancer)
Evaluating the efficacy of few-shot learning for GPT-4Vision in neurodegenerative disease histopathology: A comparative analysis with convolutional neural network model)
Evaluating artificial intelligence-enhanced digital urine cytology for bladder cancer diagnosis)
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