Advances in the application of multi-omics and machine learning technologies in sepsis research
Sepsis is one of the major global health challenges, with its complex pathological mechanisms and multi -organ dysfunction posing serious threats to patient survival. In recent years, the combination of multiomics technologies and machine learning has led to significant breakthroughs in sepsis resea...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Lanzhou University Press
2024-12-01
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| Series: | 生物医学转化 |
| Subjects: | |
| Online Access: | http://swyxzh.ijournals.cn/swyxzh/article/html/20240406 |
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| _version_ | 1841543726874230784 |
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| author | Chen Pengpeng Yang Jie Jin Xinhao Zhang Bo Yang Suibi Hong Yucai Ni Hongying Zhang Zhongheng |
| author_facet | Chen Pengpeng Yang Jie Jin Xinhao Zhang Bo Yang Suibi Hong Yucai Ni Hongying Zhang Zhongheng |
| author_sort | Chen Pengpeng |
| collection | DOAJ |
| description | Sepsis is one of the major global health challenges, with its complex pathological mechanisms and multi -organ dysfunction posing serious threats to patient survival. In recent years, the combination of multiomics technologies and machine learning has led to significant breakthroughs in sepsis research, providing new prospects for early diagnosis, precise treatment, and personalized interventions. The personalized adjustments of traditional treatments, such as corticosteroids, fluid management, and antibiotics, along with the application of traditional Chinese medicine and ulinastatin in multi-omics studies, have expanded the therapeutic options for sepsis. Chinese Multi-omics Advances in Sepsis (CMAISE) integrates multi-omics data, including genomics, proteomics, and metabolomics, to explore the molecular mechanisms and biomarkers of sepsis. This review comprehensively summarizes the current applications of multi-omics technologies in sepsis research and explores the potential of machine learning in personalized treatment, offering theoretical foundations and insights for future clinical applications and research development. |
| format | Article |
| id | doaj-art-e4c57fc8f7e14187b981c57e26da0693 |
| institution | Kabale University |
| issn | 2096-8965 |
| language | zho |
| publishDate | 2024-12-01 |
| publisher | Lanzhou University Press |
| record_format | Article |
| series | 生物医学转化 |
| spelling | doaj-art-e4c57fc8f7e14187b981c57e26da06932025-01-13T07:40:27ZzhoLanzhou University Press生物医学转化2096-89652024-12-0154455710.12287/j.issn.2096-8965.20240406Advances in the application of multi-omics and machine learning technologies in sepsis researchChen Pengpeng0Yang Jie1Jin Xinhao2Zhang Bo3Yang Suibi4Hong Yucai5Ni Hongying6Zhang Zhongheng7Department of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine,Hangzhou 310000 , Zhejiang, ChinaDepartment of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine,Hangzhou 310000 , Zhejiang, ChinaDepartment of Intensive Care Unit, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine,Hangzhou 310000 , Zhejiang, ChinaDepartment of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine,Hangzhou 310000 , Zhejiang, ChinaDepartment of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine,Hangzhou 310000 , Zhejiang, ChinaDepartment of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine,Hangzhou 310000 , Zhejiang, ChinaDepartment of Critical Care Medicine, Jinhua Municipal Central Hospital, Jinhua 321036 , Zhejiang, ChinaDepartment of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine,Hangzhou 310000 , Zhejiang, China ；Key Laboratory of Precision Diagnosis and Treatment for Abdominal Infections, Hangzhou 310000 , Zhejiang, China ；School of Medicine, Shaoxing University, Shaoxing 312000 , Zhejiang, ChinaSepsis is one of the major global health challenges, with its complex pathological mechanisms and multi -organ dysfunction posing serious threats to patient survival. In recent years, the combination of multiomics technologies and machine learning has led to significant breakthroughs in sepsis research, providing new prospects for early diagnosis, precise treatment, and personalized interventions. The personalized adjustments of traditional treatments, such as corticosteroids, fluid management, and antibiotics, along with the application of traditional Chinese medicine and ulinastatin in multi-omics studies, have expanded the therapeutic options for sepsis. Chinese Multi-omics Advances in Sepsis (CMAISE) integrates multi-omics data, including genomics, proteomics, and metabolomics, to explore the molecular mechanisms and biomarkers of sepsis. This review comprehensively summarizes the current applications of multi-omics technologies in sepsis research and explores the potential of machine learning in personalized treatment, offering theoretical foundations and insights for future clinical applications and research development.http://swyxzh.ijournals.cn/swyxzh/article/html/20240406sepsismultimodalomics |
| spellingShingle | Chen Pengpeng Yang Jie Jin Xinhao Zhang Bo Yang Suibi Hong Yucai Ni Hongying Zhang Zhongheng Advances in the application of multi-omics and machine learning technologies in sepsis research 生物医学转化 sepsis multimodal omics |
| title | Advances in the application of multi-omics and machine learning technologies in sepsis research |
| title_full | Advances in the application of multi-omics and machine learning technologies in sepsis research |
| title_fullStr | Advances in the application of multi-omics and machine learning technologies in sepsis research |
| title_full_unstemmed | Advances in the application of multi-omics and machine learning technologies in sepsis research |
| title_short | Advances in the application of multi-omics and machine learning technologies in sepsis research |
| title_sort | advances in the application of multi omics and machine learning technologies in sepsis research |
| topic | sepsis multimodal omics |
| url | http://swyxzh.ijournals.cn/swyxzh/article/html/20240406 |
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