267 related articles for article (PubMed ID: 35463005)
21. Development of a web-based calculator to predict three-month mortality among patients with bone metastases from cancer of unknown primary: An internally and externally validated study using machine-learning techniques.
Cui Y; Wang Q; Shi X; Ye Q; Lei M; Wang B
Front Oncol; 2022; 12():1095059. PubMed ID: 36568149
[TBL] [Abstract][Full Text] [Related]
22. The predictors of death within 1 year in acute ischemic stroke patients based on machine learning.
Wang K; Gu L; Liu W; Xu C; Yin C; Liu H; Rong L; Li W; Wei X
Front Neurol; 2023; 14():1092534. PubMed ID: 36908612
[TBL] [Abstract][Full Text] [Related]
23. Incorporation of a machine learning pathological diagnosis algorithm into the thyroid ultrasound imaging data improves the diagnosis risk of malignant thyroid nodules.
Li W; Hong T; Fang J; Liu W; Liu Y; He C; Li X; Xu C; Wang B; Chen Y; Sun C; Li W; Kang W; Yin C
Front Oncol; 2022; 12():968784. PubMed ID: 36568189
[TBL] [Abstract][Full Text] [Related]
24. The Construction and Validation of a new Predictive Model for Overall Survival of Clear Cell Renal Cell Carcinoma Patients with Bone Metastasis Based on Machine Learning Algorithm.
Le Y; Xu W; Guo W
Technol Cancer Res Treat; 2023; 22():15330338231165131. PubMed ID: 37078130
[TBL] [Abstract][Full Text] [Related]
25. Application of machine learning techniques in real-world research to predict the risk of liver metastasis in rectal cancer.
Qiu B; Su XH; Qin X; Wang Q
Front Oncol; 2022; 12():1065468. PubMed ID: 36605425
[TBL] [Abstract][Full Text] [Related]
26. Application of Machine Learning Algorithms to Predict Lymph Node Metastasis in Early Gastric Cancer.
Tian H; Ning Z; Zong Z; Liu J; Hu C; Ying H; Li H
Front Med (Lausanne); 2021; 8():759013. PubMed ID: 35118083
[TBL] [Abstract][Full Text] [Related]
27. A tool for predicting overall survival in patients with Ewing sarcoma: a multicenter retrospective study.
Li W; Dong S; Lin Y; Wu H; Chen M; Qin C; Li K; Zhang J; Tang ZR; Wang H; Huo K; Xie X; Hu Z; Kuang S; Yin C
BMC Cancer; 2022 Aug; 22(1):914. PubMed ID: 35999524
[TBL] [Abstract][Full Text] [Related]
28. Development of machine learning models to predict lymph node metastases in major salivary gland cancers.
Costantino A; Canali L; Festa BM; Kim SH; Spriano G; De Virgilio A
Eur J Surg Oncol; 2023 Sep; 49(9):106965. PubMed ID: 37393130
[TBL] [Abstract][Full Text] [Related]
29. Application of machine learning algorithms to predict lymph node metastasis in gastric neuroendocrine neoplasms.
Liu L; Liu W; Jia Z; Li Y; Wu H; Qu S; Zhu J; Liu X; Xu C
Heliyon; 2023 Oct; 9(10):e20928. PubMed ID: 37928390
[TBL] [Abstract][Full Text] [Related]
30. A machine learning-based model for predicting the risk of early-stage inguinal lymph node metastases in patients with squamous cell carcinoma of the penis.
Ding L; Zhang C; Wang K; Zhang Y; Wu C; Xia W; Li S; Li W; Wang J
Front Surg; 2023; 10():1095545. PubMed ID: 37009612
[TBL] [Abstract][Full Text] [Related]
31. An easy-to-use artificial intelligence preoperative lymph node metastasis predictor (LN-MASTER) in rectal cancer based on a privacy-preserving computing platform: multicenter retrospective cohort study.
Guan X; Yu G; Zhang W; Wen R; Wei R; Jiao S; Zhao Q; Lou Z; Hao L; Liu E; Gao X; Wang G; Zhang W; Wang X
Int J Surg; 2023 Mar; 109(3):255-265. PubMed ID: 36927812
[TBL] [Abstract][Full Text] [Related]
32. [A nomogram for predicting lymph node metastasis in early gastric cancer].
Cui H; Cao B; Deng H; Liu GB; Liang WQ; Xie TY; Ye L; Zhang QP; Wang N; Liu FD; Wei B
Zhonghua Wei Chang Wai Ke Za Zhi; 2022 Jan; 25(1):40-47. PubMed ID: 35067033
[No Abstract] [Full Text] [Related]
33. Machine learning-based gray-level co-occurrence matrix signature for predicting lymph node metastasis in undifferentiated-type early gastric cancer.
Wei X; Yan XJ; Guo YY; Zhang J; Wang GR; Fayyaz A; Yu J
World J Gastroenterol; 2022 Sep; 28(36):5338-5350. PubMed ID: 36185632
[TBL] [Abstract][Full Text] [Related]
34. Machine Learning-Based Shear Wave Elastography Elastic Index (SWEEI) in Predicting Cervical Lymph Node Metastasis of Papillary Thyroid Microcarcinoma: A Comparative Analysis of Five Practical Prediction Models.
Huang X; Zhang Y; He D; Lai L; Chen J; Zhang T; Mao H
Cancer Manag Res; 2022; 14():2847-2858. PubMed ID: 36171862
[TBL] [Abstract][Full Text] [Related]
35. Predict Lymph Node Metastasis in Penile Cancer Using Clinicopathological Factors and Nomograms.
Shao Y; Tu X; Liu Y; Bao Y; Ren S; Yang Z; Hu X; Wu K; Zeng H; Wei Q; Li X
Cancer Manag Res; 2021; 13():7429-7437. PubMed ID: 34594135
[TBL] [Abstract][Full Text] [Related]
36. Prediction of lymph node metastasis in patients with breast invasive micropapillary carcinoma based on machine learning and SHapley Additive exPlanations framework.
Jiang C; Xiu Y; Qiao K; Yu X; Zhang S; Huang Y
Front Oncol; 2022; 12():981059. PubMed ID: 36185290
[TBL] [Abstract][Full Text] [Related]
37. Development and Validation of a Novel Clinical Prediction Model to Predict the Risk of Lung Metastasis from Ewing Sarcoma for Medical Human-Computer Interface.
Li W; Hong T; Xu C; Wang B; Hu Z; Liu Q; Wang H; Dong S; Kang W; Yin C
Comput Intell Neurosci; 2022; 2022():1888586. PubMed ID: 35392046
[TBL] [Abstract][Full Text] [Related]
38. Clinicopathological models for predicting lymph node metastasis in patients with early-stage lung adenocarcinoma: the application of machine learning algorithms.
Chong Y; Wu Y; Liu J; Han C; Gong L; Liu X; Liang N; Li S
J Thorac Dis; 2021 Jul; 13(7):4033-4042. PubMed ID: 34422333
[TBL] [Abstract][Full Text] [Related]
39. Comparison of Machine Learning and Logic Regression Algorithms for Predicting Lymph Node Metastasis in Patients with Gastric Cancer: A two-Center Study.
Lu T; Fang Y; Liu H; Chen C; Li T; Lu M; Song D
Technol Cancer Res Treat; 2024; 23():15330338231222331. PubMed ID: 38190617
[TBL] [Abstract][Full Text] [Related]
40. Prediction of lung metastases in thyroid cancer using machine learning based on SEER database.
Liu W; Wang S; Ye Z; Xu P; Xia X; Guo M
Cancer Med; 2022 Jun; 11(12):2503-2515. PubMed ID: 35191613
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]