Below are the most recent publications written about "Machine Learning" by people in Profiles.
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Fares MY, Liu HH, da Silva Etges APB, Zhang B, Warner JJP, Olson JJ, Fedorka CJ, Khan AZ, Best MJ, Kirsch JM, Simon JE, Sanders B, Costouros JG, Zhang X, Jones P, Haas DA, Abboud JA. Utility of Machine Learning, Natural Language Processing, and Artificial Intelligence in Predicting Hospital Readmissions After Orthopaedic Surgery: A Systematic Review and Meta-Analysis. JBJS Rev. 2024 Aug 01; 12(8).
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Kroshus-Havril E, Leeds DD, McAllister TW, Kerr ZY, Knight K, Register-Mihalik JK, Lynall RC, D'Lauro C, Ho Y, Rahman M, Broglio SP, McCrea MA, Schmidt JD, Port N, Campbell D, Putukian M, Chrisman SPD, Cameron KL, Susmarski AJ, Goldman JT, Benjamin H, Buckley T, Kaminski T, Clugston JR, Feigenbaum L, Eckner JT, Mihalik JP, Kontos A, McDevitt J, Brooks MA, Rowson S, Miles C, Lintner L, Kelly L, Master C. Optimizing Concussion Care Seeking: Using Machine Learning to Predict Delayed Concussion Reporting. Am J Sports Med. 2024 Jul; 52(9):2372-2383.
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Hamaya R, Wang M, Juraschek SP, Mukamal KJ, Manson JE, Tobias DK, Sun Q, Curhan GC, Willett WC, Rimm EB, Cook NR. Prediction of 24-Hour Urinary Sodium Excretion Using Machine-Learning Algorithms. J Am Heart Assoc. 2024 May 21; 13(10):e034310.
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Wolff C, Langenhan K, Wolff M, Efimova E, Zach?us M, Darma A, Dinov B, Seew?ster T, Nedios S, Bertagnolli L, Wolff J, Paetsch I, Jahnke C, Bollmann A, Hindricks G, Bode K, Halm U, Arya A. Incidence and predictors of thermal oesophageal and vagus nerve injuries in Ablation Index-guided high-power-short-duration ablation of atrial fibrillation: a prospective study. Europace. 2024 May 02; 26(5).
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Gao Y, Dong K, Gao Y, Jin X, Yang J, Yan G, Liu Q. Unified cross-modality integration and analysis of T?cell receptors and T?cell transcriptomes by low-resource-aware representation learning. Cell Genom. 2024 May 08; 4(5):100553.
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Wang Z, Sperling MR, Wyeth D, Guez A. Automated Seizure Detection Based on State-Space Model Identification. Sensors (Basel). 2024 Mar 16; 24(6).
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Brankovic A, Huang W, Cook D, Khanna S, Bialkowski K. Elucidating Discrepancy in Explanations of Predictive Models Developed Using EMR. Stud Health Technol Inform. 2024 Jan 25; 310:865-869.
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Chang RS, Nguyen S, Chen Z, Foster E, Kwan P. Role of machine learning in the management of epilepsy: a systematic review protocol. BMJ Open. 2024 Jan 25; 14(1):e079785.
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Lee T, Wollstein G, Madu CT, Wronka A, Zheng L, Zambrano R, Schuman JS, Hu J. Reducing Ophthalmic Health Disparities Through Transfer Learning: A Novel Application to Overcome Data Inequality. Transl Vis Sci Technol. 2023 Dec 01; 12(12):2.
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Lost J, Verma T, Jekel L, von Reppert M, Tillmanns N, Merkaj S, Petersen GC, Bahar R, Gordem A, Haider MA, Subramanian H, Brim W, Ikuta I, Omuro A, Conte GM, Marquez-Nostra BV, Avesta A, Bousabarah K, Nabavizadeh A, Kazerooni AF, Aneja S, Bakas S, Lin M, Sabel M, Aboian M. Systematic Literature Review of Machine Learning Algorithms Using Pretherapy Radiologic Imaging for Glioma Molecular Subtype Prediction. AJNR Am J Neuroradiol. 2023 Oct; 44(10):1126-1134.