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Journal Abstract Search

254 related items for PubMed ID: 39187569

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  • 3. Development and application of a machine learning-based predictive model for obstructive sleep apnea screening.
    Liu K, Geng S, Shen P, Zhao L, Zhou P, Liu W.
    Front Big Data; 2024; 7():1353469. PubMed ID: 38817683
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  • 4. Diagnostic Performance of Machine Learning-Derived OSA Prediction Tools in Large Clinical and Community-Based Samples.
    Holfinger SJ, Lyons MM, Keenan BT, Mazzotti DR, Mindel J, Maislin G, Cistulli PA, Sutherland K, McArdle N, Singh B, Chen NH, Gislason T, Penzel T, Han F, Li QY, Schwab R, Pack AI, Magalang UJ.
    Chest; 2022 Mar; 161(3):807-817. PubMed ID: 34717928
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  • 5. Can Statistical Machine Learning Algorithms Help for Classification of Obstructive Sleep Apnea Severity to Optimal Utilization of Polysomnography Resources?
    Bozkurt S, Bostanci A, Turhan M.
    Methods Inf Med; 2017 Aug 11; 56(4):308-318. PubMed ID: 28590499
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  • 8. A Machine Learning Prediction Model of Adult Obstructive Sleep Apnea Based on Systematically Evaluated Common Clinical Biochemical Indicators.
    Huang J, Zhuang J, Zheng H, Yao L, Chen Q, Wang J, Fan C.
    Nat Sci Sleep; 2024 Aug 11; 16():413-428. PubMed ID: 38699466
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  • 10. Application and interpretation of machine learning models in predicting the risk of severe obstructive sleep apnea in adults.
    Shi Y, Zhang Y, Cao Z, Ma L, Yuan Y, Niu X, Su Y, Xie Y, Chen X, Xing L, Hei X, Liu H, Wu S, Li W, Ren X.
    BMC Med Inform Decis Mak; 2023 Oct 19; 23(1):230. PubMed ID: 37858225
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  • 13. Pre-Operative Ability of Clinical Scores to Predict Obstructive Sleep Apnea (OSA) Severity in Susceptible Surgical Patients.
    Deflandre E, Degey S, Brichant JF, Donneau AF, Frognier R, Poirrier R, Bonhomme V.
    Obes Surg; 2017 Mar 19; 27(3):716-729. PubMed ID: 27599985
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  • 14. Screening for Obstructive Sleep Apnea Risk by Using Machine Learning Approaches and Anthropometric Features.
    Tsai CY, Huang HT, Cheng HC, Wang J, Duh PJ, Hsu WH, Stettler M, Kuan YC, Lin YT, Hsu CR, Lee KY, Kang JH, Wu D, Lee HC, Wu CJ, Majumdar A, Liu WT.
    Sensors (Basel); 2022 Nov 09; 22(22):. PubMed ID: 36433227
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  • 16. A prediction model based on an artificial intelligence system for moderate to severe obstructive sleep apnea.
    Sun LM, Chiu HW, Chuang CY, Liu L.
    Sleep Breath; 2011 Sep 09; 15(3):317-23. PubMed ID: 20602177
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  • 18. Predicting Nondiagnostic Home Sleep Apnea Tests Using Machine Learning.
    Stretch R, Ryden A, Fung CH, Martires J, Liu S, Balasubramanian V, Saedi B, Hwang D, Martin JL, Della Penna N, Zeidler MR.
    J Clin Sleep Med; 2019 Nov 15; 15(11):1599-1608. PubMed ID: 31739849
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  • 19. Inclusion of blood pressure parameter increases predictive capability of severe obstructive sleep apnea: A decision tree approach.
    Cheng HJ, Li CY, Lin CY.
    J Clin Hypertens (Greenwich); 2024 Sep 15; 26(9):1090-1097. PubMed ID: 39037154
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  • 20. [Construction of a predictive model for in-hospital mortality of sepsis patients in intensive care unit based on machine learning].
    Zhu M, Hu C, He Y, Qian Y, Tang S, Hu Q, Hao C.
    Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2023 Jul 15; 35(7):696-701. PubMed ID: 37545445
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