Antibiotic combinations prediction based on machine learning to multicentre clinical data and drug interaction correlation-Reference-Cited by-同舟云学术

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Antibiotic combinations prediction based on machine learning to multicentre clinical data and drug interaction correlation

Published:2024-05 Issue:5 Volume:63 Page:107122
ISSN:0924-8579
Container-title:International Journal of Antimicrobial Agents
language:en
Short-container-title:International Journal of Antimicrobial Agents

Author:

Qin Jia'an,Yang Yuhe,Ai Chao,Ji Zhaoshuai,Chen Wei,Song Yingchang,Zeng Jiayu,Duan Meili,Qi Wenjie,Zhang Shutian,An Zhuoling,Lin Yang,Xu Sha,Deng Kejun,Lin Hao^ORCID,Yan Dan^ORCID

Funder

National Natural Science Foundation of China

Beijing Postdoctoral Research Foundation

Publisher

Elsevier BV

Reference20 articles.

1. Appropriateness of antibiotic prescriptions in ambulatory care in China: a nationwide descriptive database study;Zhao;Lancet Infect Dis,2021

2. Computational models, databases and tools for antibiotic combinations;Lv;Brief Bioinform,2022

3. Species-specific activity of antibacterial drug combinations;Brochado;Nature,2018

4. Machine learning methods, databases and tools for drug combination prediction;Wu;Brief Bioinform,2022

5. Minimizing treatment-induced emergence of antibiotic resistance in bacterial infections;Stracy;Science,2022

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