The experimental findings demonstrate the feasibility of automating opinion and sentiment detection in medical literature, highlighting the potential of hybrid approaches that combine programmatic data extraction and AI-driven text interpretation for large-scale biomedical knowledge synthesis.
This approach combines semantic understanding of clinical narratives with structural modeling of patient-disease-treatment relationships and successfully validates synthetic EHR data utility for privacy-preserving healthcare AI development while addressing critical requirements necessary for clinical decision support s...
U. Luke, P. Asuquo, Victor Anaga et al.· E3S Web of Conferences· 0 citations
This work outlines a framework for plausibility-aware AI that treats extracted claims not as final answers but as auditable evidence objects, making clear what was measured, how much it changed, in which setting, with what uncertainty, and from which source.
N. S. Babaiha, Stefan Geißler, Marie-Christine Simon et al.· 0 citations
This work presents a scalable, reproducible framework for evaluating, optimizing, and interpreting LLMs for biomedical knowledge extraction, with a focus on gene–gene regulatory relation prediction, pathway component recognition, multimodal pathway figure understanding, and automated prompt optimization.
Medical coding is very important for billing, record keeping, and data analysis in health care organizations. But doing the by manually takes a long time and can lead to mistakes. In this, an automated medical coding system that helps in suggesting correct ICD-10 codes from clinical text. To understand medical terms, t...
Snehal Paranjape, Sagar B. Shinde, Viraj D. Patil et al.· International Conference on...· 0 citations
: Biomedical texts naturally contain multiple biological and medical concepts within a document, resulting in a semantically rich and complex structure. Consequently, multi-label text classification (MLTC) has become a suitable framework for comprehensively modeling biomedical texts, including clinical reports, laborat...
ABSTRACT Large language models (LLMs) represent a type of generative artificial intelligence (GenAI) that generate and interpret text, with some LLMs able to process multimodal content (e.g., images, audio, video), and can be deployed as part of agents to perform users' tasks. LLMs can perform natural language processi...
J. Gwinnutt, R. D. de Oliveira, Miriam J. Haviland et al.· Pharmacoepidemiology and Dru...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.