首页|New Artificial Intelligence Study Results from Yale University School of Medicin e Described (Artificial Intelligence-aided Steatosis Assessment In Donor Livers According To the Banff Consensus Recommendations)
New Artificial Intelligence Study Results from Yale University School of Medicin e Described (Artificial Intelligence-aided Steatosis Assessment In Donor Livers According To the Banff Consensus Recommendations)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Research findings on Artificial Intelligence are discussed in a new report. According to news reporting out of New Haven, Connect icut, by NewsRx editors, research stated, “Severe macrovesicular steatosis in do nor livers is associated with primary graft dysfunction. The Banff Working Group on Liver Allograft Pathology has proposed recommendations for steatosis assessm ent of donor liver biopsy specimens with a consensus for defining ‘large droplet fat’ (LDF) and a 3-step algorithmic approach.” Our news journalists obtained a quote from the research from the Yale University School of Medicine, “We retrieved slides and initial pathology reports from pot ential liver donor biopsy specimens from 2010 to 2021. Following the Banff appro ach, we reevaluated LDF steatosis and employed a computer-assisted manual quanti fication protocol and artificial intelligence (AI) model for analysis. In a tota l of 113 slides from 88 donors, no to mild (<33% ) macrovesicular steatosis was reported in 88.5% (100/113) of slid es; 8.8% (10/113) was reported as at least moderate steatosis (> = 33%) initially. Subsequent pathology evaluation, following the Ba nff recommendation, revealed that all slides had LDF below 33%, a f inding confirmed through computer-assisted manual quantification and an AI model . Correlation coefficients between pathologist and computer-assisted manual quan tification, between computer-assisted manual quantification and the AI model, an d between the AI model and pathologist were 0.94, 0.88, and 0.81, respectively ( P <.0001 for all). The 3-step approach proposed by the Ban ff Working Group on Liver Allograft Pathology may be followed when evaluating st eatosis in donor livers.”
New HavenConnecticutUnited StatesN orth and Central AmericaArtificial IntelligenceEmerging TechnologiesHealth and MedicineMachine LearningPathologySteatosisYale University School of Medicine
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