Posts Tagged ‘Machine Learning’
Relationship Between Cognitive Impairment and Depression Among Middle Aged and Older Adults in Primary Care.
Link: https://doi.org/10.1177/23337214231214217 Authors: Federman, Alex D; Becker, Jacqueline; Carnavali, Fernando; Rivera Mindt, Monica; Cho, Dayeon; Pandey, Gaurav; Chan, Lili; Curtis, Laura; Wolf, Michael S; Wisnivesky, Juan P Abstract:
Read MorePublication: Machine Learning Boosts Precision in Social Determinants of Health Analysis
Area-level social determinants of health (SDOH) based on patients’ ZIP codes or census tracts have been commonly used in research instead of individual SDOHs. However, using area-level SDOH measures as a substitute for individual SDOH measures may not be appropriate, especially in highly diverse urban neighbourhoods like New York City. On February 8, 2024, a…
Read MoreAssociations between Sperm Epigenetic Age and Semen Parameters: An Evaluation of Clinical and Non-Clinical Cohorts.
Link: https://doi.org/10.3390/cimb46020101 Authors: Sawant, Savni; Oluwayiose, Oladele A; Nowak, Karolina; Maxwell, DruAnne L; Houle, Emily; Paskavitz, Amanda L; Saddiki, Hachem; Bertolla, Ricardo P; Pilsner, J Richard Abstract:
Read MoreComparison of predicting cardiovascular disease hospitalization using individual, ZIP code-derived, and machine learning model-predicted educational attainment in New York City.
Link: https://doi.org/10.1371/journal.pone.0297919 Authors: Takkavatakarn, Kullaya; Dai, Yang; Hsun Wen, Huei; Kauffman, Justin; Charney, Alexander; Coca, Steven G; Nadkarni, Girish N; Chan, Lili Abstract: Area-level social determinants of health (SDOH) based on patients’ ZIP codes or census tracts have been commonly used in research instead of individual SDOHs. To our knowledge, whether machine learning (ML) could…
Read MoreMachine learning models to predict end-stage kidney disease in chronic kidney disease stage 4.
Link: https://doi.org/10.1186/s12882-023-03424-7 Authors: Takkavatakarn, Kullaya; Oh, Wonsuk; Cheng, Ella; Nadkarni, Girish N; Chan, Lili Abstract: End-stage kidney disease (ESKD) is associated with increased morbidity and mortality. Identifying patients with stage 4 CKD (CKD4) at risk of rapid progression to ESKD remains challenging. Accurate prediction of CKD4 progression can improve patient outcomes by improving advanced care…
Read MoreJoint Modeling of Social Determinants and Clinical Factors to Define Subphenotypes in Out-of-Hospital Cardiac Arrest Survival: Cluster Analysis.
Link: https://doi.org/10.2196/51844 Authors: Abbott, Ethan E; Oh, Wonsuk; Dai, Yang; Feuer, Cole; Chan, Lili; Carr, Brendan G; Nadkarni, Girish N Abstract: Machine learning clustering offers an unbiased approach to better understand the interactions of complex social and clinical variables via integrative subphenotypes, an approach not studied in out-of-hospital cardiac arrest (OHCA). We conducted a cluster…
Read MorePost-operative urinary retention is impacted by neuromuscular block reversal agent choice: A retrospective cohort study in US hospital setting.
Link: https://doi.org/S0952-8180(23)00294-5 Authors: Bash, Lori D; Turzhitsky, Vladimir; Mark, Robert J; Hofer, Ira S; Weingarten, Toby N Abstract: Perioperative neuromuscular blocking agents are pharmacologically reversed to minimize complications associated with residual neuromuscular block. Neuromuscular block reversal with anticholinesterases (e.g., neostigmine) require coadministration of an anticholinergic agent (e.g., glycopyrrolate) to mitigate muscarinic activity; however, sugammadex, devoid…
Read MoreDevelopment of the ehive Digital Health App: Protocol for a Centralized Research Platform.
Link: https://doi.org/10.2196/49204 Authors: Hirten, Robert P; Danieletto, Matteo; Landell, Kyle; Zweig, Micol; Golden, Eddye; Orlov, Georgy; Rodrigues, Jovita; Alleva, Eugenia; Ensari, Ipek; Bottinger, Erwin; Nadkarni, Girish N; Fuchs, Thomas J; Fayad, Zahi A Abstract: The increasing use of smartphones, wearables, and connected devices has enabled the increasing application of digital technologies for research. Remote digital…
Read MorePer- and polyfluoroalkyl substances (PFAS) exposure and thyroid cancer risk.
Link: https://doi.org/10.1016/j.ebiom.2023.104831 Authors: van Gerwen, Maaike; Colicino, Elena; Guan, Haibin; Dolios, Georgia; Nadkarni, Girish N; Vermeulen, Roel C H; Wolff, Mary S; Arora, Manish; Genden, Eric M; Petrick, Lauren M Abstract: Although per- and polyfluoroalkyl substances (PFAS) exposure is a potential contributor to the increasing thyroid cancer trend, limited studies have investigated the association between…
Read MoreDevelopment and Validation of a Formative Assessment Tool for Nephrology Fellows’ Clinical Reasoning.
Link: https://doi.org/10.2215/CJN.0000000000000315 Authors: Boyle, Suzanne M; Martindale, James; Parsons, Andrew S; Sozio, Stephen M; Hilburg, Rachel; Bahrainwala, Jehan; Chan, Lili; Stern, Lauren D; Warburton, Karen M Abstract: Diagnostic errors are commonly driven by failures in clinical reasoning. Deficits in clinical reasoning are common among graduate medical learners, including nephrology fellows. We created and validated an…
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