Clinical documentation is essential for patient care but remains a major administrative burden for healthcare providers. This session explores how AI‑driven automation can generate structured SOAP (Subjective, Objective, Assessment, and Plan) notes from unstructuredinputs such as physician dictation and ambient patient‑doctor conversations. The solution architecture is based on an AWS infrastructure backbone to provide for scalability and compliance, with a John Snow Labs Medical LLM to generate results more accurately than general‑purpose LLMs.
Clinical documentation is essential for patient care but remains a major administrative burden for healthcare providers. This session explores how AI‑driven automation can generate structured SOAP (Subjective, Objective, Assessment, and...
The convergence of artificial intelligence and wearable healthcare devices is revolutionizing patient care by enabling continuous monitoring, early disease detection, and personalized interventions. This presentation delves into the transformative potential...
Agentic AI is transforming insurance claims processing, enabling automation, scalability, and cost efficiency. This talk explores how RAG LLMs power specialized AI agents for Auto Bodily Injury, Workers’ Compensation, and...
Hallucination, and explainability in LLM are considered to be the most important threats when deploying production grade Agentic AI model in healthcare. We present here a new architecture approach combining Graph RAG, Medical Ontologies, fined‑tuned...
In an era where artificial intelligence is reshaping communication, audio deepfakes have emerged as both a groundbreaking innovation and a formidable security threat. Advances in generative AI now enable the...
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