Summary of The Role Of Language Models in Modern Healthcare: a Comprehensive Review, by Amna Khalid et al.
The Role of Language Models in Modern Healthcare: A Comprehensive Review
by Amna Khalid, Ayma Khalid, Umar Khalid
First submitted to arxiv on: 25 Sep 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Computation and Language (cs.CL)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper examines the application of large language models (LLMs) in healthcare, highlighting their capabilities in processing complex medical data and providing insights for clinical decision-making. The authors discuss the strengths and challenges of LLMs in healthcare, including their potential to enhance patient interaction and diagnostics. Furthermore, they explore the necessary steps to ensure ethical and effective integration of LLMs into medical practice. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper talks about how big language models can help doctors and hospitals by understanding and generating medical reports, diagnoses, and conversations with patients. It looks back at how these models have improved over time and what makes them good for healthcare tasks. The authors also discuss the problems that come with using these models in medicine, like keeping patient information private, avoiding bias, and making sure they’re used correctly. |
