0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The application of artificial intelligence in the management of sepsis

      review-article
      , , , , , , , , , ,
      Medical Review
      De Gruyter
      diagnosis, treatment, sepsis, artificial intelligence

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Sepsis is a complex and heterogeneous syndrome that remains a serious challenge to healthcare worldwide. Patients afflicted by severe sepsis or septic shock are customarily placed under intensive care unit (ICU) supervision, where a multitude of apparatus is poised to produce high-granularity data. This reservoir of high-quality data forms the cornerstone for the integration of AI into clinical practice. However, existing reviews currently lack the inclusion of the latest advancements. This review examines the evolving integration of artificial intelligence (AI) in sepsis management. Applications of artificial intelligence include early detection, subtyping analysis, precise treatment and prognosis assessment. AI-driven early warning systems provide enhanced recognition and intervention capabilities, while profiling analyzes elucidate distinct sepsis manifestations for targeted therapy. Precision medicine harnesses the potential of artificial intelligence for pathogen identification, antibiotic selection, and fluid optimization. In conclusion, the seamless amalgamation of artificial intelligence into the domain of sepsis management heralds a transformative shift, ushering in novel prospects to elevate diagnostic precision, therapeutic efficacy, and prognostic acumen. As AI technologies develop, their impact on shaping the future of sepsis care warrants ongoing research and thoughtful implementation.

          Related collections

          Most cited references70

          • Record: found
          • Abstract: found
          • Article: found

          The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3).

          Definitions of sepsis and septic shock were last revised in 2001. Considerable advances have since been made into the pathobiology (changes in organ function, morphology, cell biology, biochemistry, immunology, and circulation), management, and epidemiology of sepsis, suggesting the need for reexamination.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            PhysioBank, PhysioToolkit, and PhysioNet

            Circulation, 101(23)
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              High-performance medicine: the convergence of human and artificial intelligence

              Eric Topol (2019)
              The use of artificial intelligence, and the deep-learning subtype in particular, has been enabled by the use of labeled big data, along with markedly enhanced computing power and cloud storage, across all sectors. In medicine, this is beginning to have an impact at three levels: for clinicians, predominantly via rapid, accurate image interpretation; for health systems, by improving workflow and the potential for reducing medical errors; and for patients, by enabling them to process their own data to promote health. The current limitations, including bias, privacy and security, and lack of transparency, along with the future directions of these applications will be discussed in this article. Over time, marked improvements in accuracy, productivity, and workflow will likely be actualized, but whether that will be used to improve the patient-doctor relationship or facilitate its erosion remains to be seen.
                Bookmark

                Author and article information

                Contributors
                Journal
                Med Rev (2021)
                Med Rev (2021)
                mr
                mr
                Medical Review
                De Gruyter
                2097-0773
                2749-9642
                28 November 2023
                October 2023
                : 3
                : 5
                : 369-380
                Affiliations
                deptDepartment of Emergency Medicine, Sir Run Run Shaw Hospital , universityZhejiang University School of Medicine , Hangzhou, Zhenjiang Province, China
                universityDuke University School of Medicine , Durham, NC, USA
                deptDepartment of Computer Science and Engineering , universityThe Ohio State University , Columbus, OH, USA
                deptSaw Swee Hock School of Public Health and Institute of Data science , universityNational University of Singapore , Singapore, Singapore
                Author notes
                Corresponding author: Zhongheng Zhang, deptDepartment of Emergency Medicine, Sir Run Run Shaw Hospital , universityZhejiang University School of Medicine , Hangzhou, Zhenjiang Province, China, E-mail: zh_zhang1984@ 123456zju.edu.cn .
                Author information
                https://orcid.org/0009-0006-9846-5448
                https://orcid.org/0000-0002-4601-0779
                https://orcid.org/0000-0002-2336-5323
                Article
                mr-2023-0039
                10.1515/mr-2023-0039
                10811352
                38283255
                30e561a9-8eef-4046-b6be-8df1411f5077
                © 2023 the author(s), published by De Gruyter, Berlin/Boston

                This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

                History
                : 22 August 2023
                : 8 November 2023
                Page count
                Figures: 03, Tables: 03, References: 70, Pages: 12
                Funding
                Funded by: the Fundamental Research Funds for the Central Universities
                Award ID: 226–2022-00148
                Funded by: the Project of Drug Clinical Evaluate Research of Chinese Pharmaceutical Association
                Funded by: National Natural Science Foundation of China
                Award ID: 82272180
                Funded by: the China National Key Research and Development Program
                Award ID: 2022YFC2504500
                Funded by: The Open Foundation of Key Laboratory of Digital Technology in Medical Diagnostics of Zhejiang Province
                Award ID: SZZD202206
                Funded by: Health Science and Technology Plan of Zhejiang Province
                Award ID: 2021KY745
                Categories
                Review

                diagnosis,treatment,sepsis,artificial intelligence
                diagnosis, treatment, sepsis, artificial intelligence

                Comments

                Comment on this article