Improving primary healthcare with generative AI

IF 58.7 1区医学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY

Nature Medicine Pub Date : 2024-09-18 DOI:10.1038/s41591-024-03257-3

Winnie Yip

引用次数: 0

Abstract

Studies in China show how large language models can improve primary healthcare systems, but equitably scaling this technology will require attention to rural, low-resource settings and the companion policies that support its implementation.

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利用生成式人工智能改善初级医疗保健

中国的研究表明，大型语言模型可以改善初级医疗保健系统，但要公平地推广这项技术，需要关注农村、低资源环境以及支持其实施的配套政策。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Nature Medicine 医学-生化与分子生物学

CiteScore

100.90

自引率

0.70%

发文量

525

审稿时长

1 months

期刊介绍： Nature Medicine is a monthly journal publishing original peer-reviewed research in all areas of medicine. The publication focuses on originality, timeliness, interdisciplinary interest, and the impact on improving human health. In addition to research articles, Nature Medicine also publishes commissioned content such as News, Reviews, and Perspectives. This content aims to provide context for the latest advances in translational and clinical research, reaching a wide audience of M.D. and Ph.D. readers. All editorial decisions for the journal are made by a team of full-time professional editors. Nature Medicine consider all types of clinical research, including: -Case-reports and small case series -Clinical trials, whether phase 1, 2, 3 or 4 -Observational studies -Meta-analyses -Biomarker studies -Public and global health studies Nature Medicine is also committed to facilitating communication between translational and clinical researchers. As such, we consider “hybrid” studies with preclinical and translational findings reported alongside data from clinical studies.