Luận văn Thạc sĩ Searching For Phenotypes Of Sepsis An Application Of Machine Learning To Electronic Health Records
➤ Gửi thông báo lỗi ⚠️ Báo cáo tài liệu vi phạmNội dung chi tiết: Luận văn Thạc sĩ Searching For Phenotypes Of Sepsis An Application Of Machine Learning To Electronic Health Records
Luận văn Thạc sĩ Searching For Phenotypes Of Sepsis An Application Of Machine Learning To Electronic Health Records
Yale UniversityEliSchoIar - A Digital Platform for Scholarly Publishing at YaleYale Medicine 'Ihesis Digital LibrarySchool of Medicine43466Searching F Luận văn Thạc sĩ Searching For Phenotypes Of Sepsis An Application Of Machine Learning To Electronic Health Records For Phenotypes Of Sepsis: An Application Of Machine Learning To Electronic Health RecordsMichaelJarvis BoyleFollow this and additional works at: https://elischolar.library.yale.edu/ymtdlRecommended CitationBoyle, Michael Jarvis, 'Searching For Phenotypes Of Sepsis: .An Application Of Machine Learnin Luận văn Thạc sĩ Searching For Phenotypes Of Sepsis An Application Of Machine Learning To Electronic Health Records g To Electronic Health Records' (2019). Ktfe Mcdiáne Thuii Digital Library. 3477.https://elischolar.bbrary.yale.edu?ymtdl/3477This Open Acoeu lhes.4 aLuận văn Thạc sĩ Searching For Phenotypes Of Sepsis An Application Of Machine Learning To Electronic Health Records
brought to you for free and open access by the School of XiedKtnc at EhScholar - A Digital Platform for Scholarly Publishing at Yale. It has been accYale UniversityEliSchoIar - A Digital Platform for Scholarly Publishing at YaleYale Medicine 'Ihesis Digital LibrarySchool of Medicine43466Searching F Luận văn Thạc sĩ Searching For Phenotypes Of Sepsis An Application Of Machine Learning To Electronic Health Records at Yale. For more information, please contact elischclarfSy-ak-.edu.Searching for Phenotypes of Sepsis:An Application of Machine Learning to Electronic HealthRecordsA Thesis Submitted to theYale University School of MedicineIn Partial Fulfillment of the Requirements for theDegree of Doctor of Medici Luận văn Thạc sĩ Searching For Phenotypes Of Sepsis An Application Of Machine Learning To Electronic Health Records nebyMichael Jarvis Boyle2019SEARCHING FOR PHENOTYPES OF SEPSIS: AN APPLICATION OF MACHINE LEARNING TO ELECTRONIC HEALTH RECORDS. Michael J. Boyle (SpoLuận văn Thạc sĩ Searching For Phenotypes Of Sepsis An Application Of Machine Learning To Electronic Health Records
nsored by R. Andrew Taylor). Department of Emergency Medicine, Yale University School of Medicine, New Haven, CT.Sepsis has historically been categoriYale UniversityEliSchoIar - A Digital Platform for Scholarly Publishing at YaleYale Medicine 'Ihesis Digital LibrarySchool of Medicine43466Searching F Luận văn Thạc sĩ Searching For Phenotypes Of Sepsis An Application Of Machine Learning To Electronic Health Records The goal of this study was to perform an exhaustive search for distinct phenotypes of sepsis using various unsupervised machine learning techniques applied to the electronic health record (EHR) data of 41,843 Yale New Haven Health System emergency department patients with infection between 2013 and Luận văn Thạc sĩ Searching For Phenotypes Of Sepsis An Application Of Machine Learning To Electronic Health Records 2016. Specifically, the aims were to develop an autoencoder to reduce the high-dimensional EHR data to a latent representation amenable to clustering,Luận văn Thạc sĩ Searching For Phenotypes Of Sepsis An Application Of Machine Learning To Electronic Health Records
and then to search for and assess the quality of clusters within that representation using various clustering methods (partitional, hierarchical, andYale UniversityEliSchoIar - A Digital Platform for Scholarly Publishing at YaleYale Medicine 'Ihesis Digital LibrarySchool of Medicine43466Searching F Luận văn Thạc sĩ Searching For Phenotypes Of Sepsis An Application Of Machine Learning To Electronic Health Records his exhaustive search, no convincing consistent clusters were found. Various clustering patterns were produced by the different methods but all had poor quality metrics, while evaluation metrics meant to find the ideal number of clusters did not agree on a consistent number but seemed to suggest few Luận văn Thạc sĩ Searching For Phenotypes Of Sepsis An Application Of Machine Learning To Electronic Health Records er than two clusters. Inspection of one promising arrangement with eight clusters did not reveal a statistically significant difference in admission rLuận văn Thạc sĩ Searching For Phenotypes Of Sepsis An Application Of Machine Learning To Electronic Health Records
ate. While it is impossible to prove a negative, these results suggest there are not distinct phenotypic clusters of sepsis.2AcknowledgementsI am indeYale UniversityEliSchoIar - A Digital Platform for Scholarly Publishing at YaleYale Medicine 'Ihesis Digital LibrarySchool of Medicine43466Searching F Luận văn Thạc sĩ Searching For Phenotypes Of Sepsis An Application Of Machine Learning To Electronic Health Records ss these ideas and serve as valuable sounding boards. This work was made possible through the generous support of the Yale Summer Research Grant.None of this would be possible, however, without the love and support of my wife,Shirin Jamshidian. This work is dedicated to her.3INTRODUCTION6Sepsis Defi Luận văn Thạc sĩ Searching For Phenotypes Of Sepsis An Application Of Machine Learning To Electronic Health Records nitions6Machine Learning and Electronic Health Records12AIMS15Yale UniversityEliSchoIar - A Digital Platform for Scholarly Publishing at YaleYale Medicine 'Ihesis Digital LibrarySchool of Medicine43466Searching FYale UniversityEliSchoIar - A Digital Platform for Scholarly Publishing at YaleYale Medicine 'Ihesis Digital LibrarySchool of Medicine43466Searching FGọi ngay
Chat zalo
Facebook