首页|Data on Sepsis Reported by Xu Zhang and Colleagues (An interpretable machine lea rning model for predicting 28-day mortality in patients with sepsis-associated l iver injury)
Data on Sepsis Reported by Xu Zhang and Colleagues (An interpretable machine lea rning model for predicting 28-day mortality in patients with sepsis-associated l iver injury)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Blood Diseases and Con ditions - Sepsis is the subject of a report. According to news originating from Luzhou, People’s Republic of China, by NewsRx correspondents, research stated, “ Sepsis-Associated Liver Injury (SALI) is an independent risk factor for death fr om sepsis. The aim of this study was to develop an interpretable machine learnin g model for early prediction of 28-day mortality in patients with SALI.” Financial supporters for this research include Sichuan Science and Technology Pr ogram, Southwest Medical University, Sichuan Science and Technology Innovation S eedling Project, Southwest Medical University and Xuyong County People’s Hospita l, Sichuan Provincial Youth Science and Technology Foundation, Sichuan Province Science and Technology Support Program, Clinical Key Specialty Construction Proj ect of the National Health Commission, Suining First People’s Hospital and South west Medical University.
LuzhouPeople’s Republic of ChinaAsiaBlood Diseases and ConditionsBloodstream InfectionCyborgsEmerging Techno logiesHealth and MedicineMachine LearningRisk and PreventionSepsisSept icemia
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