{"title":"Essential principles towards improving clinical risk assessment tools: A conversation with Uri Kartoun, PhD","authors":"Daniela Kamir","doi":"10.56012/hivc3918","DOIUrl":null,"url":null,"abstract":"Uri Kartoun (PhD in robotics, Ben Gurion University of the Negev, Israel) is a Staff Research Scientist and an IBM Master Inventor, co-developer of technologies such as MELD-Plus, EMRBots, Memory-memory (M2) Authentication, and Subpopulation-based Feature Selection. Prior to joining IBM Research in 2016, Kartoun worked at Microsoft Health Solutions Group and at Massachusetts General Hospital. EMWA Guest Editor Daniela Kamir, PhD, interviewed Kartoun about clinical risk assessment tools, organ transplant allocation disparities, and how the Model for End-Stage Liver Disease (MELD) score is used to allocate livers for transplantation. The conversation has been edited for brevity and clarity.","PeriodicalId":37384,"journal":{"name":"Medical Writing","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical Writing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.56012/hivc3918","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Health Professions","Score":null,"Total":0}
引用次数: 0
Abstract
Uri Kartoun (PhD in robotics, Ben Gurion University of the Negev, Israel) is a Staff Research Scientist and an IBM Master Inventor, co-developer of technologies such as MELD-Plus, EMRBots, Memory-memory (M2) Authentication, and Subpopulation-based Feature Selection. Prior to joining IBM Research in 2016, Kartoun worked at Microsoft Health Solutions Group and at Massachusetts General Hospital. EMWA Guest Editor Daniela Kamir, PhD, interviewed Kartoun about clinical risk assessment tools, organ transplant allocation disparities, and how the Model for End-Stage Liver Disease (MELD) score is used to allocate livers for transplantation. The conversation has been edited for brevity and clarity.
Uri Kartoun(以色列内盖夫本古里安大学机器人博士)是一名员工研究科学家和IBM Master Inventor,是MELD-Plus、EMRBots、内存-内存(M2)身份验证和基于亚种群的特征选择等技术的共同开发者。在2016年加入IBM Research之前,Kartoun曾在Microsoft Health Solutions Group和Massachusetts General Hospital工作。EMWA特邀编辑Daniela Kamir博士就临床风险评估工具、器官移植分配差异以及如何使用终末期肝病模型(MELD)评分来分配肝脏移植等问题采访了Kartoun。为简洁明了起见,以下对话经过了编辑。
期刊介绍:
Medical Writing is a quarterly publication that aims to educate and inform medical writers in Europe and beyond. Each issue focuses on a specific theme, and all issues include feature articles and regular columns on topics relevant to the practice of medical writing. We welcome articles providing practical advice to medical writers; guidelines and reviews/summaries/updates of guidelines published elsewhere; original research; opinion pieces; interviews; and review articles.