193 related articles for article (PubMed ID: 37616271)
1. Predicting the risk of hypertension using machine learning algorithms: A cross sectional study in Ethiopia.
Islam MM; Alam MJ; Maniruzzaman M; Ahmed NAMF; Ali MS; Rahman MJ; Roy DC
PLoS One; 2023; 18(8):e0289613. PubMed ID: 37616271
[TBL] [Abstract][Full Text] [Related]
2. Predicting the risk of diabetic retinopathy using explainable machine learning algorithms.
Islam MM; Rahman MJ; Rabby MS; Alam MJ; Pollob SMAI; Ahmed NAMF; Tawabunnahar M; Roy DC; Shin J; Maniruzzaman M
Diabetes Metab Syndr; 2023 Dec; 17(12):102919. PubMed ID: 38091881
[TBL] [Abstract][Full Text] [Related]
3. Machine learning algorithms identify hypokalaemia risk in people with hypertension in the United States National Health and Nutrition Examination Survey 1999-2018.
Lin Z; Cheng YT; Cheung BMY
Ann Med; 2023 Dec; 55(1):2209336. PubMed ID: 37162442
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. 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]
6. CVD22: Explainable artificial intelligence determination of the relationship of troponin to D-Dimer, mortality, and CK-MB in COVID-19 patients.
Kırboğa KK; Küçüksille EU; Naldan ME; Işık M; Gülcü O; Aksakal E
Comput Methods Programs Biomed; 2023 May; 233():107492. PubMed ID: 36965300
[TBL] [Abstract][Full Text] [Related]
7. Machine learning algorithms for predicting low birth weight in Ethiopia.
Bekele WT
BMC Med Inform Decis Mak; 2022 Sep; 22(1):232. PubMed ID: 36064400
[TBL] [Abstract][Full Text] [Related]
8. Predicting 7-day unplanned readmission in elderly patients with coronary heart disease using machine learning.
Song X; Tong Y; Luo Y; Chang H; Gao G; Dong Z; Wu X; Tong R
Front Cardiovasc Med; 2023; 10():1190038. PubMed ID: 37614939
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. 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]
11. A Machine Learning Model to Predict Length of Stay and Mortality among Diabetes and Hypertension Inpatients.
Barsasella D; Bah K; Mishra P; Uddin M; Dhar E; Suryani DL; Setiadi D; Masturoh I; Sugiarti I; Jonnagaddala J; Syed-Abdul S
Medicina (Kaunas); 2022 Oct; 58(11):. PubMed ID: 36363525
[No Abstract] [Full Text] [Related]
12. The prediction of in-hospital mortality in chronic kidney disease patients with coronary artery disease using machine learning models.
Ye Z; An S; Gao Y; Xie E; Zhao X; Guo Z; Li Y; Shen N; Ren J; Zheng J
Eur J Med Res; 2023 Jan; 28(1):33. PubMed ID: 36653875
[TBL] [Abstract][Full Text] [Related]
13. Explainable Machine Learning Techniques To Predict Amiodarone-Induced Thyroid Dysfunction Risk: Multicenter, Retrospective Study With External Validation.
Lu YT; Chao HJ; Chiang YC; Chen HY
J Med Internet Res; 2023 Feb; 25():e43734. PubMed ID: 36749620
[TBL] [Abstract][Full Text] [Related]
14. Cancer Metastasis Prediction and Genomic Biomarker Identification through Machine Learning and eXplainable Artificial Intelligence in Breast Cancer Research.
Yagin B; Yagin FH; Colak C; Inceoglu F; Kadry S; Kim J
Diagnostics (Basel); 2023 Oct; 13(21):. PubMed ID: 37958210
[TBL] [Abstract][Full Text] [Related]
15. Machine learning algorithm for characterizing risks of hypertension, at an early stage in Bangladesh.
Islam MM; Rahman MJ; Chandra Roy D; Tawabunnahar M; Jahan R; Ahmed NAMF; Maniruzzaman M
Diabetes Metab Syndr; 2021; 15(3):877-884. PubMed ID: 33892404
[TBL] [Abstract][Full Text] [Related]
16. Prevalence and associated anthropometric and lifestyle predictors of hypertension among adults in Kombolcha town and suburbs, Northeast Ethiopia: a community-based cross-sectional study.
Hassen B; Mamo H
BMC Cardiovasc Disord; 2019 Oct; 19(1):241. PubMed ID: 31664909
[TBL] [Abstract][Full Text] [Related]
17. Co-occurrence of hypertension and type 2 diabetes: prevalence and associated factors among Haramaya University employees in Eastern Ethiopia.
Motuma A; Gobena T; Roba KT; Berhane Y; Worku A; Regassa LD; Tolera A
Front Public Health; 2023; 11():1038694. PubMed ID: 37497022
[TBL] [Abstract][Full Text] [Related]
18. Application of information theoretic feature selection and machine learning methods for the development of genetic risk prediction models.
Jalali-Najafabadi F; Stadler M; Dand N; Jadon D; Soomro M; Ho P; Marzo-Ortega H; Helliwell P; Korendowych E; Simpson MA; Packham J; Smith CH; Barker JN; McHugh N; Warren RB; Barton A; Bowes J; ;
Sci Rep; 2021 Dec; 11(1):23335. PubMed ID: 34857774
[TBL] [Abstract][Full Text] [Related]
19. Explainable machine learning model for predicting skeletal muscle loss during surgery and adjuvant chemotherapy in ovarian cancer.
Hsu WH; Ko AT; Weng CS; Chang CL; Jan YT; Lin JB; Chien HJ; Lin WC; Sun FJ; Wu KP; Lee J
J Cachexia Sarcopenia Muscle; 2023 Oct; 14(5):2044-2053. PubMed ID: 37435785
[TBL] [Abstract][Full Text] [Related]
20. Development and validation of explainable machine-learning models for carotid atherosclerosis early screening.
Yun K; He T; Zhen S; Quan M; Yang X; Man D; Zhang S; Wang W; Han X
J Transl Med; 2023 May; 21(1):353. PubMed ID: 37246225
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
