827 related articles for article (PubMed ID: 35387629)
1. Prediction of metabolic and pre-metabolic syndromes using machine learning models with anthropometric, lifestyle, and biochemical factors from a middle-aged population in Korea.
Kim J; Mun S; Lee S; Jeong K; Baek Y
BMC Public Health; 2022 Apr; 22(1):664. PubMed ID: 35387629
[TBL] [Abstract][Full Text] [Related]
2. Machine-learning model predicting quality of life using multifaceted lifestyles in middle-aged South Korean adults: a cross-sectional study.
Kim J; Jeong K; Lee S; Baek Y
BMC Public Health; 2024 Jan; 24(1):159. PubMed ID: 38212741
[TBL] [Abstract][Full Text] [Related]
3. Development and Validation of an Insulin Resistance Predicting Model Using a Machine-Learning Approach in a Population-Based Cohort in Korea.
Park S; Kim C; Wu X
Diagnostics (Basel); 2022 Jan; 12(1):. PubMed ID: 35054379
[TBL] [Abstract][Full Text] [Related]
4. A Risk Prediction Model for Physical Restraints Among Older Chinese Adults in Long-term Care Facilities: Machine Learning Study.
Wang J; Chen H; Wang H; Liu W; Peng D; Zhao Q; Xiao M
J Med Internet Res; 2023 Apr; 25():e43815. PubMed ID: 37023416
[TBL] [Abstract][Full Text] [Related]
5. Metabolic Syndrome Prediction Models Using Machine Learning and Sasang Constitution Type.
Park JE; Mun S; Lee S
Evid Based Complement Alternat Med; 2021; 2021():8315047. PubMed ID: 33628316
[TBL] [Abstract][Full Text] [Related]
6. Issue of Data Imbalance on Low Birthweight Baby Outcomes Prediction and Associated Risk Factors Identification: Establishment of Benchmarking Key Machine Learning Models With Data Rebalancing Strategies.
Ren Y; Wu D; Tong Y; López-DeFede A; Gareau S
J Med Internet Res; 2023 May; 25():e44081. PubMed ID: 37256674
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Use of Multiprognostic Index Domain Scores, Clinical Data, and Machine Learning to Improve 12-Month Mortality Risk Prediction in Older Hospitalized Patients: Prospective Cohort Study.
Woodman RJ; Bryant K; Sorich MJ; Pilotto A; Mangoni AA
J Med Internet Res; 2021 Jun; 23(6):e26139. PubMed ID: 34152274
[TBL] [Abstract][Full Text] [Related]
9. Metabolic syndrome prediction using non-invasive and dietary parameters based on a support vector machine.
Mohseni-Takalloo S; Mozaffari-Khosravi H; Mohseni H; Mirzaei M; Hosseinzadeh M
Nutr Metab Cardiovasc Dis; 2024 Jan; 34(1):126-135. PubMed ID: 37949713
[TBL] [Abstract][Full Text] [Related]
10. The effect of data balancing approaches on the prediction of metabolic syndrome using non-invasive parameters based on random forest.
Mohseni-Takalloo S; Mohseni H; Mozaffari-Khosravi H; Mirzaei M; Hosseinzadeh M
BMC Bioinformatics; 2024 Jan; 25(1):18. PubMed ID: 38212697
[TBL] [Abstract][Full Text] [Related]
11. Machine Learning Hybrid Model for the Prediction of Chronic Kidney Disease.
Khalid H; Khan A; Zahid Khan M; Mehmood G; Shuaib Qureshi M
Comput Intell Neurosci; 2023; 2023():9266889. PubMed ID: 36959840
[TBL] [Abstract][Full Text] [Related]
12. Machine learning-based models to predict the conversion of normal blood pressure to hypertension within 5-year follow-up.
Andishgar A; Bazmi S; Tabrizi R; Rismani M; Keshavarzian O; Pezeshki B; Ahmadizar F
PLoS One; 2024; 19(3):e0300201. PubMed ID: 38483860
[TBL] [Abstract][Full Text] [Related]
13. Comparing machine learning algorithms to predict COVID‑19 mortality using a dataset including chest computed tomography severity score data.
Zakariaee SS; Naderi N; Ebrahimi M; Kazemi-Arpanahi H
Sci Rep; 2023 Jul; 13(1):11343. PubMed ID: 37443373
[TBL] [Abstract][Full Text] [Related]
14. Breast cancer prediction with transcriptome profiling using feature selection and machine learning methods.
Taghizadeh E; Heydarheydari S; Saberi A; JafarpoorNesheli S; Rezaeijo SM
BMC Bioinformatics; 2022 Oct; 23(1):410. PubMed ID: 36183055
[TBL] [Abstract][Full Text] [Related]
15. Study on risk factors of diabetic peripheral neuropathy and establishment of a prediction model by machine learning.
Lian X; Qi J; Yuan M; Li X; Wang M; Li G; Yang T; Zhong J
BMC Med Inform Decis Mak; 2023 Aug; 23(1):146. PubMed ID: 37533059
[TBL] [Abstract][Full Text] [Related]
16. Machine Learning to Predict the Progression of Bone Mass Loss Associated with Personal Characteristics and a Metabolic Syndrome Scoring Index.
Cheng CH; Lin CY; Cho TH; Lin CM
Healthcare (Basel); 2021 Jul; 9(8):. PubMed ID: 34442085
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Risk prediction model of metabolic syndrome in perimenopausal women based on machine learning.
Xiaoxue W; Zijun W; Shichen C; Mukun Y; Yi C; Linqing M; Wenpei B
Int J Med Inform; 2024 May; 188():105480. PubMed ID: 38754284
[TBL] [Abstract][Full Text] [Related]
19. Joint modeling strategy for using electronic medical records data to build machine learning models: an example of intracerebral hemorrhage.
Tang J; Wang X; Wan H; Lin C; Shao Z; Chang Y; Wang H; Wu Y; Zhang T; Du Y
BMC Med Inform Decis Mak; 2022 Oct; 22(1):278. PubMed ID: 36284327
[TBL] [Abstract][Full Text] [Related]
20. Disability risk prediction model based on machine learning among Chinese healthy older adults: results from the China Health and Retirement Longitudinal Study.
Han Y; Wang S
Front Public Health; 2023; 11():1271595. PubMed ID: 38026309
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]