arXiv:2607. 05644v1 Announce Type: cross Abstract: Natural language processing (NLP) is a common method for supplying data to clinical research and decision making by extracting information from electronic medical records.
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arXiv:2608.28608v1 Announce Type: cross Abstract: Ancient Indian medical texts like Sushruta Samhita have extensive information on diseases, treatments, and surgical techniques. Yet, their ancient fo...
arXiv:2606. 19602v1 Announce Type: new Abstract: Patient contexts span hundreds of heterogeneous documents and thousands of structured data points, yet the document-level metadata that AI systems need for retrieval and triage is absent or incomplete.
arXiv:2512.08617v2 Announce Type: replace Abstract: This tutorial focused on Healthcare Domain Applications of NLP, what we have achieved around HealthcareNLP, and the challenges that lie ahead for t...
arXiv:2607. 04907v1 Announce Type: new Abstract: Deploying Large Language Models (LLMs) in high-stakes clinical settings remains limited by structural hallucinations, weak deterministic reasoning over tabular patient data, and omissions in vector retrieval.
arXiv:2604. 25374v2 Announce Type: replace-cross Abstract: Background: Dutch medical corpora are scarce, limiting NLP development.
arXiv:2609.00296v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly proposed for healthcare tasks such as clinical documentation, evidence retrieval, patient messaging,...