Recognize use cases for generative artificial intelligence (AI) in medicine that could augment human clinicians, such as automated medical coding or care pathway optimization. |
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Assess public health burden and financial impact of diagnostic errors and misdiagnosis-related harms. |
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Discuss practical strategies to develop responsible and ethical generative AI solutions in healthcare. |
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List advantages that generative models may provide over other AI techniques for addressing complex challenges in areas like medical imaging, precision oncology insights and patient-provider conversations. |
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Apply techniques to help detect and reduce fabricated "hallucinated" content in generative AI model outputs in medicine, including human-in-the-loop validation and uncertainty-aware model architectures. |
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Identify potential pitfalls of applying AI for clinical diagnosis without adequate guardrails. |
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Implement prerequisites and systems of care essential to deploying AI to achieve diagnostic excellence. |
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Identify current and future AI projects for consideration at Baptist Health. |
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Implement strategies to optimize collaboration, communication and coordination among residents, fellows, students, physicians and healthcare professionals engaging in the acquisition of knowledge. |
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