Corrigendum to “Automatic Detection of Severely and Mildly Infected COVID-19 Patients with Supervised Machine Learning Models” [IRBM (2023) 100725]

IF 5.6 4区医学 Q1 ENGINEERING, BIOMEDICAL

Irbm Pub Date : 2024-11-08 DOI:10.1016/j.irbm.2024.100869

Mehmet Tahir Huyut

引用次数: 0

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利用监督机器学习模型自动检测重度和轻度感染 COVID-19 患者"[IRBM (2023) 100725] 更正

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

Irbm ENGINEERING, BIOMEDICAL-

CiteScore

10.30

自引率

4.20%

发文量

审稿时长

57 days

期刊介绍： IRBM is the journal of the AGBM (Alliance for engineering in Biology an Medicine / Alliance pour le génie biologique et médical) and the SFGBM (BioMedical Engineering French Society / Société française de génie biologique médical) and the AFIB (French Association of Biomedical Engineers / Association française des ingénieurs biomédicaux). As a vehicle of information and knowledge in the field of biomedical technologies, IRBM is devoted to fundamental as well as clinical research. Biomedical engineering and use of new technologies are the cornerstones of IRBM, providing authors and users with the latest information. Its six issues per year propose reviews (state-of-the-art and current knowledge), original articles directed at fundamental research and articles focusing on biomedical engineering. All articles are submitted to peer reviewers acting as guarantors for IRBM''s scientific and medical content. The field covered by IRBM includes all the discipline of Biomedical engineering. Thereby, the type of papers published include those that cover the technological and methodological development in: -Physiological and Biological Signal processing (EEG, MEG, ECG…)- Medical Image processing- Biomechanics- Biomaterials- Medical Physics- Biophysics- Physiological and Biological Sensors- Information technologies in healthcare- Disability research- Computational physiology- …