198 related articles for article (PubMed ID: 38613173)
21. Application of Artificial Intelligence for Preoperative Diagnostic and Prognostic Prediction in Epithelial Ovarian Cancer Based on Blood Biomarkers.
Kawakami E; Tabata J; Yanaihara N; Ishikawa T; Koseki K; Iida Y; Saito M; Komazaki H; Shapiro JS; Goto C; Akiyama Y; Saito R; Saito M; Takano H; Yamada K; Okamoto A
Clin Cancer Res; 2019 May; 25(10):3006-3015. PubMed ID: 30979733
[TBL] [Abstract][Full Text] [Related]
22. Application of machine learning algorithm in predicting distant metastasis of T1 gastric cancer.
Tian H; Liu Z; Liu J; Zong Z; Chen Y; Zhang Z; Li H
Sci Rep; 2023 Apr; 13(1):5741. PubMed ID: 37029221
[TBL] [Abstract][Full Text] [Related]
23. Identifying Explainable Machine Learning Models and a Novel SFRP2
Yang Z; Zhou D; Huang J
Int J Mol Sci; 2023 Nov; 24(23):. PubMed ID: 38069266
[TBL] [Abstract][Full Text] [Related]
24. Exploring risk factors for cervical lymph node metastasis in papillary thyroid microcarcinoma: construction of a novel population-based predictive model.
Huang Y; Mao Y; Xu L; Wen J; Chen G
BMC Endocr Disord; 2022 Nov; 22(1):269. PubMed ID: 36329470
[TBL] [Abstract][Full Text] [Related]
25. Prediction of Acute Respiratory Distress Syndrome in Traumatic Brain Injury Patients Based on Machine Learning Algorithms.
Wang R; Cai L; Zhang J; He M; Xu J
Medicina (Kaunas); 2023 Jan; 59(1):. PubMed ID: 36676795
[No Abstract] [Full Text] [Related]
26. Prediction of subjective cognitive decline after corpus callosum infarction by an interpretable machine learning-derived early warning strategy.
Xu Y; Sun X; Liu Y; Huang Y; Liang M; Sun R; Yin G; Song C; Ding Q; Du B; Bi X
Front Neurol; 2023; 14():1123607. PubMed ID: 37416313
[TBL] [Abstract][Full Text] [Related]
27. Establishment and validation of a heart failure risk prediction model for elderly patients after coronary rotational atherectomy based on machine learning.
Zhang L; Zhou X; Cao J
PeerJ; 2024; 12():e16867. PubMed ID: 38313005
[TBL] [Abstract][Full Text] [Related]
28. 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]
29. Interpretable machine learning model for early prediction of 28-day mortality in ICU patients with sepsis-induced coagulopathy: development and validation.
Zhou S; Lu Z; Liu Y; Wang M; Zhou W; Cui X; Zhang J; Xiao W; Hua T; Zhu H; Yang M
Eur J Med Res; 2024 Jan; 29(1):14. PubMed ID: 38172962
[TBL] [Abstract][Full Text] [Related]
30. 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]
31. Hospital mortality prediction in traumatic injuries patients: comparing different SMOTE-based machine learning algorithms.
Hassanzadeh R; Farhadian M; Rafieemehr H
BMC Med Res Methodol; 2023 Apr; 23(1):101. PubMed ID: 37087425
[TBL] [Abstract][Full Text] [Related]
32. A machine learning-based model for predicting distant metastasis in patients with rectal cancer.
Qiu B; Shen Z; Wu S; Qin X; Yang D; Wang Q
Front Oncol; 2023; 13():1235121. PubMed ID: 37655097
[TBL] [Abstract][Full Text] [Related]
33. 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]
34. Identification of prognostic signatures in remnant gastric cancer through an interpretable risk model based on machine learning: a multicenter cohort study.
Zhan Z; Chen B; Cheng H; Xu S; Huang C; Zhou S; Chen H; Lin X; Lin R; Huang W; Ma X; Fu Y; Chen Z; Zheng H; Shi S; Guo Z; Zhang L
BMC Cancer; 2024 Apr; 24(1):547. PubMed ID: 38689252
[TBL] [Abstract][Full Text] [Related]
35. Prediction model of obstructive sleep apnea-related hypertension: Machine learning-based development and interpretation study.
Shi Y; Ma L; Chen X; Li W; Feng Y; Zhang Y; Cao Z; Yuan Y; Xie Y; Liu H; Yin L; Zhao C; Wu S; Ren X
Front Cardiovasc Med; 2022; 9():1042996. PubMed ID: 36545020
[TBL] [Abstract][Full Text] [Related]
36. An External-Validated Prediction Model to Predict Lung Metastasis among Osteosarcoma: A Multicenter Analysis Based on Machine Learning.
Li W; Liu W; Hussain Memon F; Wang B; Xu C; Dong S; Wang H; Hu Z; Quan X; Deng Y; Liu Q; Su S; Yin C
Comput Intell Neurosci; 2022; 2022():2220527. PubMed ID: 35571720
[TBL] [Abstract][Full Text] [Related]
37. Automated machine learning for predicting liver metastasis in patients with gastrointestinal stromal tumor: a SEER-based analysis.
Liu L; Zhang R; Shi Y; Sun J; Xu X
Sci Rep; 2024 May; 14(1):12415. PubMed ID: 38816560
[TBL] [Abstract][Full Text] [Related]
38. Supervised learning applied to classifying fallers versus non-fallers among older adults with cancer.
Ramsdale E; Kunduru M; Smith L; Culakova E; Shen J; Meng S; Zand M; Anand A
J Geriatr Oncol; 2023 May; 14(4):101498. PubMed ID: 37084629
[TBL] [Abstract][Full Text] [Related]
39. Predictive model and risk analysis for coronary heart disease in people living with HIV using machine learning.
Liu Z; Meng Z; Wei D; Qin Y; Lv Y; Xie L; Qiu H; Xie B; Li L; Wei X; Zhang D; Liang B; Li W; Qin S; Yan T; Meng Q; Wei H; Jiang G; Su L; Jiang N; Zhang K; Lv J; Hu Y
BMC Med Inform Decis Mak; 2024 Apr; 24(1):110. PubMed ID: 38664736
[TBL] [Abstract][Full Text] [Related]
40. Effects of heavy metal exposure on hypertension: A machine learning modeling approach.
Li W; Huang G; Tang N; Lu P; Jiang L; Lv J; Qin Y; Lin Y; Xu F; Lei D
Chemosphere; 2023 Oct; 337():139435. PubMed ID: 37422210
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]