A Machine Learning Approach for Emergency Detection in Medical Scenarios Using Large Language Models
Authors:
- 18 November 2025
- book chapter
- Published by Springer Nature
- p. 186-199
Abstract
No abstract availableKeywords
All Related Versions
This publication has 16 references indexed in Scilit:
- Security Analysis and Improvement of Authenticated Key Agreement Protocol for Remote Patient Monitoring IoMT2024
- Large Language Models for Healthcare: Applications, Models, Datasets, and Challenges2024
- A new approach for automatic test case generation from use case diagram using LLMs and prompt engineering2024
- An LLM's Medical Testing Recommendations in a Nigerian Clinic: Potential and Limits of Prompt Engineering for Clinical Decision Support2024
- AI-powered Emergency Keyword Detection for Autonomous Vehicles2024
- Rationalism in the face of GPT hypes: Benchmarking the output of large language models against human expert-curated biomedical knowledge graphsArtificial Intelligence in the Life Sciences, 2024
- A Comprehensive Review of AI in Healthcare: Exploring Neural Networks in Medical Imaging, LLM-Based Interactive Response Systems, NLP-Based EHR Systems, Ethics, and Beyond2023
- Enhancing Emergency Response Through Speech Emotion Recognition: A Machine Learning Approach2023
- Early detection of emergency events from social media: a new text clustering approachNatural Hazards, 2022
- Deep ensemble multitask classification of emergency medical call incidents combining multimodal data improves emergency medical dispatchArtificial Intelligence in Medicine, 2021