Posts Tagged ‘Machine Learning’
2024 Update of the RECOVER-Adult Long COVID Research Index.
Link: https://doi.org/10.1001/jama.2024.24184 Authors: Geng, Linda N; Erlandson, Kristine M; Hornig, Mady; Letts, Rebecca; Selvaggi, Caitlin; Ashktorab, Hassan; Atieh, Ornina; Bartram, Logan; Brim, Hassan; Brosnahan, Shari B; Brown, Jeanette; Castro, Mario; Charney, Alexander; Chen, Peter; Deeks, Steven G; Erdmann, Nathaniel; Flaherman, Valerie J; Ghamloush, Maher A; Goepfert, Paul; Goldman, Jason D; Han, Jenny E; Hess, Rachel;…
Read MoreThe role of deep learning in diagnostic imaging of spondyloarthropathies: a systematic review.
Link: https://doi.org/10.1007/s00330-024-11261-x Authors: Omar, Mahmud; Watad, Abdulla; McGonagle, Dennis; Soffer, Shelly; Glicksberg, Benjamin S; Nadkarni, Girish N; Klang, Eyal Abstract: Diagnostic imaging is an integral part of identifying spondyloarthropathies (SpA), yet the interpretation of these images can be challenging. This review evaluated the use of deep learning models to enhance the diagnostic accuracy of SpA…
Read MoreDeep Learning for Contrast Enhanced Mammography – A Systematic Review.
Link: https://doi.org/10.1016/j.acra.2024.11.035 Authors: Sorin, Vera; Sklair-Levy, Miri; Glicksberg, Benjamin S; Konen, Eli; Nadkarni, Girish N; Klang, Eyal Abstract: Contrast-enhanced mammography (CEM) is a relatively novel imaging technique that enables both anatomical and functional breast imaging, with improved diagnostic performance compared to standard 2D mammography. The aim of this study is to systematically review the literature…
Read MoreExtracting International Classification of Diseases Codes from Clinical Documentation using Large Language Models.
Link: https://doi.org/10.1055/a-2491-3872 Authors: Simmons, Ashley; Takkavatakarn, Kullaya; McDougal, Megan; Dilcher, Brian; Pincavitch, Jami; Meadows, Lukas; Kauffman, Justin; Klang, Eyal; Wig, Rebecca; Smith, Gordon Stephen; Soroush, Ali; Freeman, Robert; Apakama, Donald; Charney, Alexander; Kohli-Seth, Roopa; Nadkarni, Girish; Sakhuja, Ankit Abstract: Large language models (LLMs) have shown promise in various professional fields, including medicine and law. However,…
Read MoreA Primer on Reinforcement Learning in Medicine for Clinicians.
Link: https://doi.org/10.1038/s41746-024-01316-0 Authors: Jayaraman, Pushkala; Desman, Jacob; Sabounchi, Moein; Nadkarni, Girish N; Sakhuja, Ankit Abstract: Reinforcement Learning (RL) is a machine learning paradigm that enhances clinical decision-making for healthcare professionals by addressing uncertainties and optimizing sequential treatment strategies. RL leverages patient-data to create personalized treatment plans, improving outcomes and resource efficiency. This review introduces RL…
Read MoreBenchmarking Large Language Models for Extraction of International Classification of Diseases Codes from Clinical Documentation.
Link: https://doi.org/10.1101/2024.04.29.24306573 Authors: Simmons, Ashley; Takkavatakarn, Kullaya; McDougal, Megan; Dilcher, Brian; Pincavitch, Jami; Meadows, Lukas; Kauffman, Justin; Klang, Eyal; Wig, Rebecca; Smith, Gordon; Soroush, Ali; Freeman, Robert; Apakama, Donald J; Charney, Alexander W; Kohli-Seth, Roopa; Nadkarni, Girish N; Sakhuja, Ankit Abstract: Healthcare reimbursement and coding is dependent on accurate extraction of International Classification of Diseases-tenth…
Read MoreDetection of neurologic changes in critically ill infants using deep learning on video data: a retrospective single center cohort study.
Link: https://doi.org/10.1016/j.eclinm.2024.102919 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 physical exam, which can be intermittent and subjective.…
Read MoreLeveraging Artificial Intelligence and Data Science for Integration of Social Determinants of Health in Emergency Medicine: Scoping Review.
Link: https://doi.org/10.2196/57124 Authors: Abbott, Ethan E; Apakama, Donald; Richardson, Lynne D; Chan, Lili; Nadkarni, Girish N Abstract: Social determinants of health (SDOH) are critical drivers of health disparities and patient outcomes. However, accessing and collecting patient-level SDOH data can be operationally challenging in the emergency department (ED) clinical setting, requiring innovative approaches. This scoping review…
Read MoreApplications of ChatGPT in Heart Failure Prevention, Diagnosis, Management, and Research: A Narrative Review.
Link: https://doi.org/10.3390/diagnostics14212393 Authors: Ghanta, Sai Nikhila; Al’Aref, Subhi J; Lala-Trinidade, Anuradha; Nadkarni, Girish N; Ganatra, Sarju; Dani, Sourbha S; Mehta, Jawahar L Abstract: Heart failure (HF) is a leading cause of mortality, morbidity, and financial burden worldwide. The emergence of advanced artificial intelligence (AI) technologies, particularly Generative Pre-trained Transformer (GPT) systems, presents new opportunities to…
Read MoreAutomated Identification of Heart Failure With Reduced Ejection Fraction Using Deep Learning-Based Natural Language Processing.
Link: https://doi.org/S2213-1779(24)00618-8 Authors: Nargesi, Arash A; Adejumo, Philip; Dhingra, Lovedeep Singh; Rosand, Benjamin; Hengartner, Astrid; Coppi, Andreas; Benigeri, Simon; Sen, Sounok; Ahmad, Tariq; Nadkarni, Girish N; Lin, Zhenqiu; Ahmad, Faraz S; Krumholz, Harlan M; Khera, Rohan Abstract: The lack of automated tools for measuring care quality limits the implementation of a national program to assess…
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