BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

348 related articles for article (PubMed ID: 36324086)

  • 1. Dementia risk prediction in individuals with mild cognitive impairment: a comparison of Cox regression and machine learning models.
    Wang M; Greenberg M; Forkert ND; Chekouo T; Afriyie G; Ismail Z; Smith EE; Sajobi TT
    BMC Med Res Methodol; 2022 Nov; 22(1):284. PubMed ID: 36324086
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Survival prediction models since liver transplantation - comparisons between Cox models and machine learning techniques.
    Kantidakis G; Putter H; Lancia C; Boer J; Braat AE; Fiocco M
    BMC Med Res Methodol; 2020 Nov; 20(1):277. PubMed ID: 33198650
    [TBL] [Abstract][Full Text] [Related]  

  • 3. ESKD Risk Prediction Model in a Multicenter Chronic Kidney Disease Cohort in China: A Derivation, Validation, and Comparison Study.
    Hui M; Ma J; Yang H; Gao B; Wang F; Wang J; Lv J; Zhang L; Yang L; Zhao M
    J Clin Med; 2023 Feb; 12(4):. PubMed ID: 36836039
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Predicting Colorectal Cancer Survival Using Time-to-Event Machine Learning: Retrospective Cohort Study.
    Yang X; Qiu H; Wang L; Wang X
    J Med Internet Res; 2023 Oct; 25():e44417. PubMed ID: 37883174
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Dementia prediction in the general population using clinically accessible variables: a proof-of-concept study using machine learning. The AGES-Reykjavik study.
    Twait EL; Andaur Navarro CL; Gudnason V; Hu YH; Launer LJ; Geerlings MI
    BMC Med Inform Decis Mak; 2023 Aug; 23(1):168. PubMed ID: 37641038
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers.
    Deist TM; Dankers FJWM; Valdes G; Wijsman R; Hsu IC; Oberije C; Lustberg T; van Soest J; Hoebers F; Jochems A; El Naqa I; Wee L; Morin O; Raleigh DR; Bots W; Kaanders JH; Belderbos J; Kwint M; Solberg T; Monshouwer R; Bussink J; Dekker A; Lambin P
    Med Phys; 2018 Jul; 45(7):3449-3459. PubMed ID: 29763967
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Predictive performance of machine and statistical learning methods: Impact of data-generating processes on external validity in the "large N, small p" setting.
    Austin PC; Harrell FE; Steyerberg EW
    Stat Methods Med Res; 2021 Jun; 30(6):1465-1483. PubMed ID: 33848231
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Can Predictive Modeling Tools Identify Patients at High Risk of Prolonged Opioid Use After ACL Reconstruction?
    Anderson AB; Grazal CF; Balazs GC; Potter BK; Dickens JF; Forsberg JA
    Clin Orthop Relat Res; 2020 Jul; 478(7):0-1618. PubMed ID: 32282466
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A Simulation Study to Compare the Predictive Performance of Survival Neural Networks with Cox Models for Clinical Trial Data.
    Kantidakis G; Biganzoli E; Putter H; Fiocco M
    Comput Math Methods Med; 2021; 2021():2160322. PubMed ID: 34880930
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A comparison of machine learning algorithms and traditional regression-based statistical modeling for predicting hypertension incidence in a Canadian population.
    Chowdhury MZI; Leung AA; Walker RL; Sikdar KC; O'Beirne M; Quan H; Turin TC
    Sci Rep; 2023 Jan; 13(1):13. PubMed ID: 36593280
    [TBL] [Abstract][Full Text] [Related]  

  • 11. [Efficacy of machine learning models
    Gao K; Wang Y; Cao H; Jia J
    Nan Fang Yi Ke Da Xue Xue Bao; 2023 Jun; 43(6):952-963. PubMed ID: 37439167
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Survival Analysis in Cognitively Normal Subjects and in Patients with Mild Cognitive Impairment Using a Proportional Hazards Model with Extreme Gradient Boosting Regression.
    Khajehpiri B; Moghaddam HA; Forouzanfar M; Lashgari R; Ramos-Cejudo J; Osorio RS; Ardekani BA;
    J Alzheimers Dis; 2022; 85(2):837-850. PubMed ID: 34864679
    [TBL] [Abstract][Full Text] [Related]  

  • 13. The Application and Comparison of Machine Learning Models for the Prediction of Breast Cancer Prognosis: Retrospective Cohort Study.
    Xiao J; Mo M; Wang Z; Zhou C; Shen J; Yuan J; He Y; Zheng Y
    JMIR Med Inform; 2022 Feb; 10(2):e33440. PubMed ID: 35179504
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Which model is better in predicting the survival of laryngeal squamous cell carcinoma?: Comparison of the random survival forest based on machine learning algorithms to Cox regression: analyses based on SEER database.
    Sun H; Wu S; Li S; Jiang X
    Medicine (Baltimore); 2023 Mar; 102(10):e33144. PubMed ID: 36897699
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Predicting Cognitive Impairment and Dementia: A Machine Learning Approach.
    Aschwanden D; Aichele S; Ghisletta P; Terracciano A; Kliegel M; Sutin AR; Brown J; Allemand M
    J Alzheimers Dis; 2020; 75(3):717-728. PubMed ID: 32333585
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Machine learning approaches to studying the role of cognitive reserve in conversion from mild cognitive impairment to dementia.
    Facal D; Valladares-Rodriguez S; Lojo-Seoane C; Pereiro AX; Anido-Rifon L; Juncos-Rabadán O
    Int J Geriatr Psychiatry; 2019 Jul; 34(7):941-949. PubMed ID: 30854737
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Machine Learning Did Not Outperform Conventional Competing Risk Modeling to Predict Revision Arthroplasty.
    Oosterhoff JHF; de Hond AAH; Peters RM; van Steenbergen LN; Sorel JC; Zijlstra WP; Poolman RW; Ring D; Jutte PC; Kerkhoffs GMMJ; Putter H; Steyerberg EW; Doornberg JN;
    Clin Orthop Relat Res; 2024 Mar; ():. PubMed ID: 38470976
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Sample size and predictive performance of machine learning methods with survival data: A simulation study.
    Infante G; Miceli R; Ambrogi F
    Stat Med; 2023 Dec; 42(30):5657-5675. PubMed ID: 37947168
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Statistical models versus machine learning for competing risks: development and validation of prognostic models.
    Kantidakis G; Putter H; Litière S; Fiocco M
    BMC Med Res Methodol; 2023 Feb; 23(1):51. PubMed ID: 36829145
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Empirical analyses and simulations showed that different machine and statistical learning methods had differing performance for predicting blood pressure.
    Austin PC; Harrell FE; Lee DS; Steyerberg EW
    Sci Rep; 2022 Jun; 12(1):9312. PubMed ID: 35660759
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 18.