Yuming Sun, Stephen Salerno, Ziyang Pan, Eileen Yang, Chinakorn Sujimongkol, Jiyeon Song, Xinan Wang, Peisong Han, Donglin Zeng, Jian Kang, David C Christiani, Yi Li
{"title":"Assessing the prognostic utility of clinical and radiomic features for COVID-19 patients admitted to ICU: challenges and lessons learned.","authors":"Yuming Sun, Stephen Salerno, Ziyang Pan, Eileen Yang, Chinakorn Sujimongkol, Jiyeon Song, Xinan Wang, Peisong Han, Donglin Zeng, Jian Kang, David C Christiani, Yi Li","doi":"10.1162/99608f92.9d86a749","DOIUrl":"10.1162/99608f92.9d86a749","url":null,"abstract":"<p><p>Severe cases of COVID-19 often necessitate escalation to the Intensive Care Unit (ICU), where patients may face grave outcomes, including mortality. Chest X-rays play a crucial role in the diagnostic process for evaluating COVID-19 patients. Our collaborative efforts with Michigan Medicine in monitoring patient outcomes within the ICU have motivated us to investigate the potential advantages of incorporating clinical information and chest X-ray images for predicting patient outcomes. We propose an analytical workflow to address challenges such as the absence of standardized approaches for image pre-processing and data utilization. We then propose an ensemble learning approach designed to maximize the information derived from multiple prediction algorithms. This entails optimizing the weights within the ensemble and considering the common variability present in individual risk scores. Our simulations demonstrate the superior performance of this weighted ensemble averaging approach across various scenarios. We apply this refined ensemble methodology to analyze post-ICU COVID-19 mortality, an occurrence observed in 21% of COVID-19 patients admitted to the ICU at Michigan Medicine. Our findings reveal substantial performance improvement when incorporating imaging data compared to models trained solely on clinical risk factors. Furthermore, the addition of radiomic features yields even larger enhancements, particularly among older and more medically compromised patients. These results may carry implications for enhancing patient outcomes in similar clinical contexts.</p>","PeriodicalId":73195,"journal":{"name":"Harvard data science review","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11225107/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141556055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Rejoinder: Building a Paradigm That Allows for the Possibility of Non-Ignorable Nonresponse","authors":"Michael A. Bailey","doi":"10.1162/99608f92.4187b1b4","DOIUrl":"https://doi.org/10.1162/99608f92.4187b1b4","url":null,"abstract":"","PeriodicalId":73195,"journal":{"name":"Harvard data science review","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135241135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Close to Refuge: Integrating AI and Human Insights for Intervention and Prevention: A Conversation With Seema Iyer","authors":"Seema Iyer, Xiao-Li Meng, Liberty Vittert","doi":"10.1162/99608f92.1a58d824","DOIUrl":"https://doi.org/10.1162/99608f92.1a58d824","url":null,"abstract":"","PeriodicalId":73195,"journal":{"name":"Harvard data science review","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136263122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Intelligence and Rationality of AI and Humans: A Conversation With Steven Pinker","authors":"Steven Pinker, Xiao-Li Meng, Liberty Vittert","doi":"10.1162/99608f92.c37d3572","DOIUrl":"https://doi.org/10.1162/99608f92.c37d3572","url":null,"abstract":"","PeriodicalId":73195,"journal":{"name":"Harvard data science review","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136263986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Crisis? What Crisis? Sociology’s Slow Progress Toward Scientific Transparency","authors":"Kim A. Weeden","doi":"10.1162/99608f92.151c41e3","DOIUrl":"https://doi.org/10.1162/99608f92.151c41e3","url":null,"abstract":"","PeriodicalId":73195,"journal":{"name":"Harvard data science review","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136317015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Demonstrations of the Potential of AI-based Political Issue Polling","authors":"Nathan E. Sanders, Alex Ulinich, Bruce Schneier","doi":"10.1162/99608f92.1d3cf75d","DOIUrl":"https://doi.org/10.1162/99608f92.1d3cf75d","url":null,"abstract":"","PeriodicalId":73195,"journal":{"name":"Harvard data science review","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136318265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Understanding and Fostering Regional Artificial Intelligence Ecosystems: A Case Study in Maine","authors":"Hamit Hamutcu, Usama Fayyad, Michael Pollastri","doi":"10.1162/99608f92.dc2a1d1b","DOIUrl":"https://doi.org/10.1162/99608f92.dc2a1d1b","url":null,"abstract":"","PeriodicalId":73195,"journal":{"name":"Harvard data science review","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136316714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nicole Lazar, James Byrns, Danielle Crowe, Meghan McGinty, Angela Abraham, Mike Guo, Megan Mann, Prithvi Narayanan, Lydia Roberts, Benjamin Sidore, Maxwell Wager
{"title":"Perils and Opportunities of ChatGPT: A High School Perspective","authors":"Nicole Lazar, James Byrns, Danielle Crowe, Meghan McGinty, Angela Abraham, Mike Guo, Megan Mann, Prithvi Narayanan, Lydia Roberts, Benjamin Sidore, Maxwell Wager","doi":"10.1162/99608f92.9f0adc39","DOIUrl":"https://doi.org/10.1162/99608f92.9f0adc39","url":null,"abstract":"","PeriodicalId":73195,"journal":{"name":"Harvard data science review","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136316681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Birth of a New Discipline: Data Science Education","authors":"Koby Mike, Benny Kimelfeld, Orit Hazzan","doi":"10.1162/99608f92.280afe66","DOIUrl":"https://doi.org/10.1162/99608f92.280afe66","url":null,"abstract":"","PeriodicalId":73195,"journal":{"name":"Harvard data science review","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136262883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}