Large Language Models (LLMs in healthcare) are AI systems trained on massive text corpora to understand, summarize and generate human-like language. In clinical environments, they function as assistive copilots-helping clinicians, administrators and operations teams process complex medical information faster and more accurately.

Healthcare data is highly unstructured and fragmented across systems: progress notes, discharge summaries, radiology reports, referral letters, prior authorizations and patient education materials. Consequently, LLMs in healthcare are most impactful where cognitive load is high and documentation is repetitive.

However, LLMs can produce confident but incorrect outputs (hallucinations). Therefore, safe healthcare AI deployment requires structured governance, human validation, traceable audit logs and secure infrastructure design.

At Logassa, we approach healthcare AI from a systems engineering perspective-ensuring scalability, interoperability and compliance across clinical workflows.