Summary of Medaide: Leveraging Large Language Models For On-premise Medical Assistance on Edge Devices, by Abdul Basit et al.
MedAide: Leveraging Large Language Models for On-Premise Medical Assistance on Edge Devices
by Abdul Basit, Khizar Hussain, Muhammad Abdullah Hanif, Muhammad Shafique
First submitted to arxiv on: 28 Feb 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: 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 This paper introduces MedAide, a novel on-premise healthcare chatbot designed for resource-constrained edge computing and embedded systems. MedAide leverages tiny-large language models (LLMs) integrated with LangChain to provide efficient edge-based preliminary medical diagnostics and support. The system employs model optimizations for minimal memory footprint and latency on embedded devices without server infrastructure. Training is optimized using low-rank adaptation (LoRA), and the model is trained on diverse medical datasets, incorporating reinforcement learning from human feedback (RLHF) to enhance domain-specific capabilities. MedAide achieves 77% accuracy in medical consultations and scores 56 on the USMLE benchmark, making it an energy-efficient healthcare assistance platform that alleviates privacy concerns due to edge-based deployment. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research creates a special kind of computer program called MedAide that helps people with health problems. The program can be used in places where there aren’t many doctors or hospitals nearby. It uses tiny computers and special language models to understand what’s wrong and give advice. To make it work well, the program was trained on lots of different medical information and tested to see how good it is. MedAide is very accurate, getting 77% of health problems right, and it can even use a special test called USMLE. This means people in remote areas can get help without having to go to a hospital or wait for a doctor. |
Keywords
» Artificial intelligence » Lora » Low rank adaptation » Reinforcement learning from human feedback » Rlhf
