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内部医学年度回顾2023年
Naruaki Ogasawara1, Kazuto Matsunaga2, Hajime Isomoto3
1Editorial Department, The Japanese Society of Internal Medicine (JSIM), Japan.
Internal medicine (Tokyo, Japan)
|September 4, 2024
概括
在2023年,内部医学看到了较少的COVID-19提交,对人工智能 (AI) 和机器学习 (ML) 对心脏病检测和预测严重的COVID-19疾病的兴趣日益增加.
科学领域:
- 内部医学 内部医学
- 医疗信息学 医疗信息学
- 心脏病学 心脏病学
背景情况:
- 内部医学杂志在2023年期间在提交重点方面经历了显著的转变.
- 较少的提交与新型冠状病毒感染 (COVID-19) 有关.
- 观察到对人工智能 (AI) 和机器学习 (ML) 研究领域的兴趣增加.
研究的目的:
- 报告2023年内部医学提交的变化格局.
- 突出AI和ML在医学研究和临床实践中的新兴作用.
- 提供期刊的提交统计数据,包括接受率.
主要方法:
- 对2023年期刊提交数据的分析.
- 审查发表的专注于AI和ML应用的文章.
- 关于提交数量和接受率的统计报告.
主要成果:
- 观察到COVID-19相关提交的情况显著下降.
- 该杂志发表了关于AI和ML的首篇文章.
- 人工智能在早期心脏病检测方面表现出潜力.
- ML在预测住院COVID-19患者的严重疾病风险方面表现有希望.
结论:
- 内部医学正在适应新的研究趋势,结合AI和ML.
- 人工智能和机器学习为医学提供了新的诊断和治疗可能性.
- 该期刊的提交趋势反映了医学研究重点的更广泛转变.
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