Posts Tagged ‘Machine Learning’
Differentiation of Prior SARS-CoV-2 Infection and Postacute Sequelae by Standard Clinical Laboratory Measurements in the RECOVER Cohort.
Link: https://doi.org/10.7326/M24-0737 Authors: Erlandson, Kristine M; Geng, Linda N; Selvaggi, Caitlin A; Thaweethai, Tanayott; Chen, Peter; Erdmann, Nathan B; Goldman, Jason D; Henrich, Timothy J; Hornig, Mady; Karlson, Elizabeth W; Katz, Stuart D; Kim, C; Cribbs, Sushma K; Laiyemo, Adeyinka O; Letts, Rebecca; Lin, Janet Y; Marathe, Jai; Parthasarathy, Sairam; Patterson, Thomas F; Taylor, Brittany…
Read MoreThe Role of Artificial Intelligence in Nephrology Clinical Trials.
Link: https://doi.org/10.1681/ASN.0000000000000486 Authors: Chan, Lili; Nadkarni, Girish N Abstract:
Read MoreDevelopment and Validation of a Policy Tree Approach for Optimizing Intravenous Fluids in Critically Ill Patients with Sepsis and Acute Kidney Injury.
Link: https://doi.org/10.1101/2024.08.06.24311556 Authors: Oh, Wonsuk; Takkavatakarn, Kullaya; Kittrell, Hannah; Shawwa, Khaled; Gomez, Hernando; Sawant, Ashwin S; Tandon, Pranai; Kumar, Gagan; Sterling, Michael; Hofer, Ira; Chan, Lili; Oropello, John; Kohli-Seth, Roopa; Charney, Alexander W; Kraft, Monica; Kovatch, Patricia; Kellum, John A; Nadkarni, Girish N; Sakhuja, Ankit Abstract: Intravenous fluids are mainstay of management of acute kidney…
Read MoreA foundation model for clinician-centered drug repurposing.
Link: https://doi.org/10.1101/2023.03.19.23287458 Authors: Huang, Kexin; Chandak, Payal; Wang, Qianwen; Havaldar, Shreyas; Vaid, Akhil; Leskovec, Jure; Nadkarni, Girish; Glicksberg, Benjamin S; Gehlenborg, Nils; Zitnik, Marinka Abstract: Drug repurposing – identifying new therapeutic uses for approved drugs – is often serendipitous and opportunistic, expanding the use of drugs for new diseases. The clinical utility of drug repurposing…
Read MorePerceptions Related to Careers in Nephrology on Student Doctor Network Using Natural Language Processing.
Link: https://doi.org/10.1016/j.ekir.2024.07.030 Authors: Takkavatakarn, Kullaya; Dai, Yang; Sridhar, Abhinaya; Borvick, Miriam; Ehrenfeld, Ricki; Cepin, Cristina Liriano; Nadkarni, Girish N; Chan, Lili Abstract:
Read MoreA foundational transformer leveraging full night, multichannel sleep study data accurately classifies sleep stages.
Link: https://doi.org/10.1101/2024.08.02.24311417 Authors: Fox, Benjamin; Jiang, Joy; Wickramaratne, Sajila; Kovatch, Patricia; Suarez-Farinas, Mayte; Shah, Neomi A; Parekh, Ankit; Nadkarni, Girish N Abstract: To investigate whether a foundational transformer model using 8-hour, multichannel data from polysomnograms can outperform existing artificial intelligence (AI) methods for sleep stage classification. We utilized the Sleep Heart Health Study (SHHS) visits…
Read MoreRole of artificial intelligence in critical care nutrition support and research.
Link: https://doi.org/10.1002/ncp.11194 Authors: Kittrell, Hannah D; Shaikh, Ahmed; Adintori, Peter A; McCarthy, Paul; Kohli-Seth, Roopa; Nadkarni, Girish N; Sakhuja, Ankit Abstract: Nutrition plays a key role in the comprehensive care of critically ill patients. Determining optimal nutrition strategy, however, remains a subject of intense debate. Artificial intelligence (AI) applications are becoming increasingly common in medicine,…
Read MoreArtificial intelligence-guided detection of under-recognized cardiomyopathies on point-of-care cardiac ultrasound: a multi-center study.
Link: https://doi.org/10.1101/2024.03.10.24304044 Authors: Oikonomou, Evangelos K; Vaid, Akhil; Holste, Gregory; Coppi, Andreas; McNamara, Robert L; Baloescu, Cristiana; Krumholz, Harlan M; Wang, Zhangyang; Apakama, Donald J; Nadkarni, Girish N; Khera, Rohan Abstract: Point-of-care ultrasonography (POCUS) enables cardiac imaging at the bedside and in communities but is limited by abbreviated protocols and variation in quality. We developed…
Read MoreAccurate prediction of neurologic changes in critically ill infants using pose AI.
Link: https://doi.org/10.1101/2024.04.17.24305953 Authors: Gleason, Alec; Richter, Florian; Beller, Nathalia; Arivazhagan, Naveen; Feng, Rui; Holmes, Emma; Glicksberg, Benjamin S; Morton, Sarah U; La Vega-Talbott, Maite; Fields, Madeline; Guttmann, Katherine; Nadkarni, Girish N; Richter, Felix Abstract: Infant alertness and neurologic changes can reflect life-threatening pathology but are assessed by exam, which can be intermittent and subjective. Reliable,…
Read MoreAssessing calibration and bias of a deployed machine learning malnutrition prediction model within a large healthcare system.
Link: https://doi.org/10.1038/s41746-024-01141-5 Authors: Liou, Lathan; Scott, Erick; Parchure, Prathamesh; Ouyang, Yuxia; Egorova, Natalia; Freeman, Robert; Hofer, Ira S; Nadkarni, Girish N; Timsina, Prem; Kia, Arash; Levin, Matthew A Abstract: Malnutrition is a frequently underdiagnosed condition leading to increased morbidity, mortality, and healthcare costs. The Mount Sinai Health System (MSHS) deployed a machine learning model (MUST-Plus)…
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