Authors: Mingyu Jin, Qinkai Yu, Chong Zhang, Dong Shu, Suiyuan Zhu, Mengnan Du, Yongfeng Zhang, Yanda Meng

Published on: February 01, 2024

Impact Score: 8.3

Arxiv code: Arxiv:2402.00746

Summary

• What is new: Introduces Heath-LLM, leveraging large-scale feature extraction and medical knowledge for improved disease prediction.
• Why this is important: Traditional intelligent healthcare is limited by its inability to fully integrate individual patient data and lacks flexibility.
• What the research proposes: Heath-LLM combines large-scale feature extraction with medical knowledge scoring to improve disease prediction and personal health management.
• Results: Outperforms traditional health management methods in disease prediction accuracy.

Technical Details

Technological frameworks used: Heath-LLM

Models used: Large-scale feature extraction models, semi-automated analytical tools

Data used: Extensive health reports

Potential Impact

Healthcare providers, medical insurance companies, health data analytics firms

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