173 related articles for article (PubMed ID: 34126702)
1. Machine Learning Model for Predicting Postoperative Survival of Patients with Colorectal Cancer.
Osman MH; Mohamed RH; Sarhan HM; Park EJ; Baik SH; Lee KY; Kang J
Cancer Res Treat; 2022 Apr; 54(2):517-524. PubMed ID: 34126702
[TBL] [Abstract][Full Text] [Related]
2. Predicting Survival of Patients With Rectal Neuroendocrine Tumors Using Machine Learning: A SEER-Based Population Study.
Cheng X; Li J; Xu T; Li K; Li J
Front Surg; 2021; 8():745220. PubMed ID: 34805260
[No Abstract] [Full Text] [Related]
3. LASSO-Based Machine Learning Algorithm for Prediction of Lymph Node Metastasis in T1 Colorectal Cancer.
Kang J; Choi YJ; Kim IK; Lee HS; Kim H; Baik SH; Kim NK; Lee KY
Cancer Res Treat; 2021 Jul; 53(3):773-783. PubMed ID: 33421980
[TBL] [Abstract][Full Text] [Related]
4. Artificial intelligence based personalized predictive survival among colorectal cancer patients.
Susič D; Syed-Abdul S; Dovgan E; Jonnagaddala J; Gradišek A
Comput Methods Programs Biomed; 2023 Apr; 231():107435. PubMed ID: 36842345
[TBL] [Abstract][Full Text] [Related]
5. A Machine Learning Algorithm for Predicting the Risk of Developing to M1b Stage of Patients With Germ Cell Testicular Cancer.
Ding L; Wang K; Zhang C; Zhang Y; Wang K; Li W; Wang J
Front Public Health; 2022; 10():916513. PubMed ID: 35844840
[TBL] [Abstract][Full Text] [Related]
6. Does the SORG Algorithm Predict 5-year Survival in Patients with Chondrosarcoma? An External Validation.
Bongers MER; Thio QCBS; Karhade AV; Stor ML; Raskin KA; Lozano Calderon SA; DeLaney TF; Ferrone ML; Schwab JH
Clin Orthop Relat Res; 2019 Oct; 477(10):2296-2303. PubMed ID: 31107338
[TBL] [Abstract][Full Text] [Related]
7. Prediction of Neurological Outcomes in Out-of-hospital Cardiac Arrest Survivors Immediately after Return of Spontaneous Circulation: Ensemble Technique with Four Machine Learning Models.
Heo JH; Kim T; Shin J; Suh GJ; Kim J; Jung YS; Park SM; Kim S;
J Korean Med Sci; 2021 Jul; 36(28):e187. PubMed ID: 34282605
[TBL] [Abstract][Full Text] [Related]
8. Using Machine Learning Approaches to Predict Short-Term Risk of Cardiotoxicity Among Patients with Colorectal Cancer After Starting Fluoropyrimidine-Based Chemotherapy.
Li C; Chen L; Chou C; Ngorsuraches S; Qian J
Cardiovasc Toxicol; 2022 Feb; 22(2):130-140. PubMed ID: 34792740
[TBL] [Abstract][Full Text] [Related]
9. Construction and validation of machine learning models for predicting distant metastases in newly diagnosed colorectal cancer patients: A large-scale and real-world cohort study.
Wei R; Yu G; Wang X; Jiang Z; Guan X
Cancer Med; 2024 Mar; 13(5):e6971. PubMed ID: 38491804
[TBL] [Abstract][Full Text] [Related]
10. Application of machine learning approaches to predict the 5-year survival status of patients with esophageal cancer.
Gong X; Zheng B; Xu G; Chen H; Chen C
J Thorac Dis; 2021 Nov; 13(11):6240-6251. PubMed ID: 34992804
[TBL] [Abstract][Full Text] [Related]
11. Development and validation of a deep learning model for predicting postoperative survival of patients with gastric cancer.
Wu M; Yang X; Liu Y; Han F; Li X; Wang J; Guo D; Tang X; Lin L; Liu C
BMC Public Health; 2024 Mar; 24(1):723. PubMed ID: 38448849
[TBL] [Abstract][Full Text] [Related]
12. Development and validation of a prognostic nomogram for colorectal cancer after surgery.
Li BW; Ma XY; Lai S; Sun X; Sun MJ; Chang B
World J Clin Cases; 2021 Jul; 9(21):5860-5872. PubMed ID: 34368305
[TBL] [Abstract][Full Text] [Related]
13. Nomograms to predict survival after colorectal cancer resection without preoperative therapy.
Zhang ZY; Luo QF; Yin XW; Dai ZL; Basnet S; Ge HY
BMC Cancer; 2016 Aug; 16(1):658. PubMed ID: 27553083
[TBL] [Abstract][Full Text] [Related]
14. Preoperative prediction of lymph node status in patients with colorectal cancer. Developing a predictive model using machine learning.
Hartwig M; Bräuner KB; Vogelsang R; Gögenur I
Int J Colorectal Dis; 2022 Dec; 37(12):2517-2524. PubMed ID: 36435940
[TBL] [Abstract][Full Text] [Related]
15. Predicting Overall Survival in Patients with Nonmetastatic Gastric Signet Ring Cell Carcinoma: A Machine Learning Approach.
Li X; Chen Z; Lin J; Wang S; Song C
Comput Math Methods Med; 2022; 2022():4862376. PubMed ID: 36148015
[TBL] [Abstract][Full Text] [Related]
16. A modified TNM staging system for non-metastatic colorectal cancer based on nomogram analysis of SEER database.
Kong X; Li J; Cai Y; Tian Y; Chi S; Tong D; Hu Y; Yang Q; Li J; Poston G; Yuan Y; Ding K
BMC Cancer; 2018 Jan; 18(1):50. PubMed ID: 29310604
[TBL] [Abstract][Full Text] [Related]
17. Computed Tomography-Based Radiomic Features Could Potentially Predict Microsatellite Instability Status in Stage II Colorectal Cancer: A Preliminary Study.
Fan S; Li X; Cui X; Zheng L; Ren X; Ma W; Ye Z
Acad Radiol; 2019 Dec; 26(12):1633-1640. PubMed ID: 30929999
[TBL] [Abstract][Full Text] [Related]
18. Predicting mortality and recurrence in colorectal cancer: Comparative assessment of predictive models.
Alinia S; Asghari-Jafarabadi M; Mahmoudi L; Roshanaei G; Safari M
Heliyon; 2024 Mar; 10(6):e27854. PubMed ID: 38515707
[TBL] [Abstract][Full Text] [Related]
19. [Prediction of intensive care unit readmission for critically ill patients based on ensemble learning].
Lin Y; Wu JY; Lin K; Hu YH; Kong GL
Beijing Da Xue Xue Bao Yi Xue Ban; 2021 Jun; 53(3):566-572. PubMed ID: 34145862
[TBL] [Abstract][Full Text] [Related]
20. Predictors of 30-Day Mortality Among Dutch Patients Undergoing Colorectal Cancer Surgery, 2011-2016.
van den Bosch T; Warps AK; de Nerée Tot Babberich MPM; Stamm C; Geerts BF; Vermeulen L; Wouters MWJM; Dekker JWT; Tollenaar RAEM; Tanis PJ; Miedema DM;
JAMA Netw Open; 2021 Apr; 4(4):e217737. PubMed ID: 33900400
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]