Database-based machine learning in sepsis deserves attention

Affiliations

¹ Jiangsu Provincial Key Laboratory of Critical Care Medicine, Department of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, No. 87, Dingjiaqiao Road, Gulou District, Nanjing, 210009, People's Republic of China.
² The State Key Laboratory of Bioelectronics, School of Instrument Science and Engineering, Southeast University, Nanjing, People's Republic of China.
³ Department of Critical Care Medicine, The First Affiliated Hospital of Soochow University, Soochow University, No. 899 Pinghai Road, Suzhou, 215000, People's Republic of China. 15905162429@163.com.

Comment

Wenhan Hu et al. Intensive Care Med. 2023 Feb.

. 2023 Feb;49(2):262-263.

doi: 10.1007/s00134-022-06961-1. Epub 2023 Jan 2.

¹ Jiangsu Provincial Key Laboratory of Critical Care Medicine, Department of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, No. 87, Dingjiaqiao Road, Gulou District, Nanjing, 210009, People's Republic of China.
² The State Key Laboratory of Bioelectronics, School of Instrument Science and Engineering, Southeast University, Nanjing, People's Republic of China.
³ Department of Critical Care Medicine, The First Affiliated Hospital of Soochow University, Soochow University, No. 899 Pinghai Road, Suzhou, 215000, People's Republic of China. 15905162429@163.com.

No abstract available

Comment in

Database-based machine learning in sepsis deserves attention. Author's reply.
Kalimouttou A, Pirracchio R. Kalimouttou A, et al. Intensive Care Med. 2023 Feb;49(2):264-265. doi: 10.1007/s00134-022-06972-y. Epub 2023 Jan 10. Intensive Care Med. 2023. PMID: 36627491 No abstract available.

Machine-learning-derived sepsis bundle of care.
Kalimouttou A, Lerner I, Cheurfa C, Jannot AS, Pirracchio R. Kalimouttou A, et al. Intensive Care Med. 2023 Jan;49(1):26-36. doi: 10.1007/s00134-022-06928-2. Epub 2022 Nov 29. Intensive Care Med. 2023. PMID: 36446854

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