BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

171 related articles for article (PubMed ID: 35677769)

  • 1. Early Prediction Model for Critical Illness of Hospitalized COVID-19 Patients Based on Machine Learning Techniques.
    Fu Y; Zhong W; Liu T; Li J; Xiao K; Ma X; Xie L; Jiang J; Zhou H; Liu R; Zhang W
    Front Public Health; 2022; 10():880999. PubMed ID: 35677769
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Development and Validation of a Clinical Risk Score to Predict the Occurrence of Critical Illness in Hospitalized Patients With COVID-19.
    Liang W; Liang H; Ou L; Chen B; Chen A; Li C; Li Y; Guan W; Sang L; Lu J; Xu Y; Chen G; Guo H; Guo J; Chen Z; Zhao Y; Li S; Zhang N; Zhong N; He J;
    JAMA Intern Med; 2020 Aug; 180(8):1081-1089. PubMed ID: 32396163
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Biological signatures and prediction of an immunosuppressive status-persistent critical illness-among orthopedic trauma patients using machine learning techniques.
    Lei M; Han Z; Wang S; Guo C; Zhang X; Song Y; Lin F; Huang T
    Front Immunol; 2022; 13():979877. PubMed ID: 36325351
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Machine learning models for predicting critical illness risk in hospitalized patients with COVID-19 pneumonia.
    Liu Q; Pang B; Li H; Zhang B; Liu Y; Lai L; Le W; Li J; Xia T; Zhang X; Ou C; Ma J; Li S; Guo X; Zhang S; Zhang Q; Jiang M; Zeng Q
    J Thorac Dis; 2021 Feb; 13(2):1215-1229. PubMed ID: 33717594
    [TBL] [Abstract][Full Text] [Related]  

  • 5. The Development and Validation of Simplified Machine Learning Algorithms to Predict Prognosis of Hospitalized Patients With COVID-19: Multicenter, Retrospective Study.
    He F; Page JH; Weinberg KR; Mishra A
    J Med Internet Res; 2022 Jan; 24(1):e31549. PubMed ID: 34951865
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Risk factors for the critical illness in SARS-CoV-2 infection: a multicenter retrospective cohort study.
    Cheng S; Wu D; Li J; Zou Y; Wan Y; Shen L; Zhu L; Shi M; Hou L; Xu T; Jiao N; Li Y; Huang Y; Tang Z; Xu M; Jiang S; Li M; Yan G; Lan P; Zhu R
    Respir Res; 2020 Oct; 21(1):277. PubMed ID: 33087114
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Utility of laboratory and immune biomarkers in predicting disease progression and mortality among patients with moderate to severe COVID-19 disease at a Philippine tertiary hospital.
    Punzalan FER; Aherrera JAM; de Paz-Silava SLM; Mondragon AV; Malundo AFG; Tan JJE; Tantengco OAG; Quebral EPB; Uy MNAR; Lintao RCV; Dela Rosa JGL; Mercado MEP; Avenilla KC; Poblete JB; Albay AB; David-Wang AS; Alejandria MM
    Front Immunol; 2023; 14():1123497. PubMed ID: 36926338
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Model-based Prediction of Critical Illness in Hospitalized Patients with COVID-19.
    Schalekamp S; Huisman M; van Dijk RA; Boomsma MF; Freire Jorge PJ; de Boer WS; Herder GJM; Bonarius M; Groot OA; Jong E; Schreuder A; Schaefer-Prokop CM
    Radiology; 2021 Jan; 298(1):E46-E54. PubMed ID: 32787701
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Machine-learning-based COVID-19 mortality prediction model and identification of patients at low and high risk of dying.
    Banoei MM; Dinparastisaleh R; Zadeh AV; Mirsaeidi M
    Crit Care; 2021 Sep; 25(1):328. PubMed ID: 34496940
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Machine Learning Predictive Modeling for the Identification of Moderate Coronavirus Disease 2019 During the Pandemic: A Retrospective Study.
    Wang T; Zhao Z; Li W; Wu J; Ye Q; Xie H
    Cureus; 2023 Dec; 15(12):e50619. PubMed ID: 38226092
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Clinical and inflammatory features based machine learning model for fatal risk prediction of hospitalized COVID-19 patients: results from a retrospective cohort study.
    Guan X; Zhang B; Fu M; Li M; Yuan X; Zhu Y; Peng J; Guo H; Lu Y
    Ann Med; 2021 Dec; 53(1):257-266. PubMed ID: 33410720
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Machine Learning Model for Risk Prediction of Community-Acquired Acute Kidney Injury Hospitalization From Electronic Health Records: Development and Validation Study.
    Hsu CN; Liu CL; Tain YL; Kuo CY; Lin YC
    J Med Internet Res; 2020 Aug; 22(8):e16903. PubMed ID: 32749223
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Utilization of machine-learning models to accurately predict the risk for critical COVID-19.
    Assaf D; Gutman Y; Neuman Y; Segal G; Amit S; Gefen-Halevi S; Shilo N; Epstein A; Mor-Cohen R; Biber A; Rahav G; Levy I; Tirosh A
    Intern Emerg Med; 2020 Nov; 15(8):1435-1443. PubMed ID: 32812204
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Machine learning model identifies aggressive acute pancreatitis within 48 h of admission: a large retrospective study.
    Yuan L; Ji M; Wang S; Wen X; Huang P; Shen L; Xu J
    BMC Med Inform Decis Mak; 2022 Nov; 22(1):312. PubMed ID: 36447180
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Early predictors of severe COVID-19 among hospitalized patients.
    Zhao Q; Yuan Y; Zhang J; Li J; Li W; Guo K; Wang Y; Chen J; Yan W; Wang B; Jing N; Ma B; Zhang Q
    J Clin Lab Anal; 2022 Feb; 36(2):e24177. PubMed ID: 34951061
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Host transcriptomics and machine learning for secondary bacterial infections in patients with COVID-19: a prospective, observational cohort study.
    Carney M; Pelaia TM; Chew T; Teoh S; Phu A; Kim K; Wang Y; Iredell J; Zerbib Y; McLean A; Schughart K; Tang B; Shojaei M; Short KR;
    Lancet Microbe; 2024 Mar; 5(3):e272-e281. PubMed ID: 38310908
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Development of a novel machine learning model based on laboratory and imaging indices to predict acute cardiac injury in cancer patients with COVID-19 infection: a retrospective observational study.
    Wan G; Wu X; Zhang X; Sun H; Yu X
    J Cancer Res Clin Oncol; 2023 Dec; 149(19):17039-17050. PubMed ID: 37747525
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort.
    Magunia H; Lederer S; Verbuecheln R; Gilot BJ; Koeppen M; Haeberle HA; Mirakaj V; Hofmann P; Marx G; Bickenbach J; Nohe B; Lay M; Spies C; Edel A; Schiefenhövel F; Rahmel T; Putensen C; Sellmann T; Koch T; Brandenburger T; Kindgen-Milles D; Brenner T; Berger M; Zacharowski K; Adam E; Posch M; Moerer O; Scheer CS; Sedding D; Weigand MA; Fichtner F; Nau C; Prätsch F; Wiesmann T; Koch C; Schneider G; Lahmer T; Straub A; Meiser A; Weiss M; Jungwirth B; Wappler F; Meybohm P; Herrmann J; Malek N; Kohlbacher O; Biergans S; Rosenberger P
    Crit Care; 2021 Aug; 25(1):295. PubMed ID: 34404458
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Early predictive factors of progression from severe type to critical ill type in patients with Coronavirus Disease 2019: A retrospective cohort study.
    Li N; Kong H; Zheng XZ; Li XY; Ma J; Zhang H; Wang DX; Li HC; Liu XM
    PLoS One; 2020; 15(12):e0243195. PubMed ID: 33264366
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Development and validation of an online model to predict critical COVID-19 with immune-inflammatory parameters.
    Gao Y; Chen L; Chi J; Zeng S; Feng X; Li H; Liu D; Feng X; Wang S; Wang Y; Yu R; Yuan Y; Xu S; Li C; Zhang W; Li S; Gao Q
    J Intensive Care; 2021 Feb; 9(1):19. PubMed ID: 33602326
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.