Efficient management of pulmonary embolism diagnosis using a two-step interconnected machine learning model based on electronic health records data

IF 5.4 3区材料科学 Q2 CHEMISTRY, PHYSICAL

ACS Applied Energy Materials Pub Date : 2024-03-06 DOI:10.1007/s13755-024-00276-9

Soroor Laffafchi, Ahmad Ebrahimi, Samira Kafan

引用次数: 0

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利用基于电子健康记录数据的两步互联机器学习模型高效管理肺栓塞诊断

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

ACS Applied Energy Materials Materials Science-Materials Chemistry

CiteScore

10.30

自引率

6.20%

发文量

1368

期刊介绍： ACS Applied Energy Materials is an interdisciplinary journal publishing original research covering all aspects of materials, engineering, chemistry, physics and biology relevant to energy conversion and storage. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important energy applications.