Learn how medical LLMs, document understanding, and reasoning models are used to extract oncology timelines, build patient cohorts, and support evidence-based cancer care with natural language querying.
Why are patient journeys critical for oncology care? Oncology care is inherently longitudinal, complex, and personalized. Each patient's history includes diagnostic imaging, pathology, lab results, clinical notes, treatment regimens, and...
How can AI governance be automated in healthcare applications of generative AI? Automating AI governance in healthcare involves embedding bias detection, robustness checks, and compliance validation directly into the development...
What is the current state of the mental health crisis? Globally, mental health disorders affect over 970 million people, according to the Global Burden of Disease Study. In the U.S.,...
Radiology is central to modern healthcare, yet its rapid growth in imaging volume has strained clinical workflows and introduced variability in diagnostic interpretation. Recent advancements in artificial intelligence, particularly in...
What is regulatory-grade de-identification in healthcare? Regulatory-grade de-identification refers to the process of systematically transforming or removing Protected Health Information (PHI) to comply with laws like HIPAA and GDPR. It...
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