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 NER, Multi Agent Models, combining both local and cloud computing for safe, secure, and efficient model deployment, using small dataset of public knowledge and real patient files in reproductive medicine in North Africa. This work is a collaborative work between public and private fertility clinics and Computer Science startup based in Tunisia. Undergoing Randomized trial is being deployed to measure the impact of Agentic AI models in managing stress and anxiety levels for patients undergoing fertility treatments.
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...
While generative AI models and applications have huge potential across healthcare, their successful deployment requires addressing several ethical, trustworthiness, and safety considerations. These concerns include domain‑specific evaluation, hallucinations, truthfulness and...
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