Similar articles for PMID: 36474302

Year	Number of Results
1915	1
1998	2
1999	1
2006	2
2008	3
2012	1
2013	2
2014	3
2015	4
2016	4
2017	9
2018	11
2019	13
2020	14
2021	14
2022	21
2023	1
2024	0

1

Machine learning identifies prominent factors associated with cardiovascular disease: findings from two million adults in the Kashgar Prospective Cohort Study (KPCS).

Li JX, Li L, Zhong X, Fan SJ, Cen T, Wang J, He C, Zhang Z, Luo YN, Liu XX, Hu LX, Zhang YD, Qiu HL, Dong GH, Zou XG, Yang BY. Li JX, et al. Glob Health Res Policy. 2022 Dec 6;7(1):48. doi: 10.1186/s41256-022-00282-y. Glob Health Res Policy. 2022. PMID: 36474302 Free PMC article.

2

Machine Learning Approach to Classify Cardiovascular Disease in Patients With Nonalcoholic Fatty Liver Disease in the UK Biobank Cohort.

Sharma D, Gotlieb N, Farkouh ME, Patel K, Xu W, Bhat M. Sharma D, et al. J Am Heart Assoc. 2022 Jan 4;11(1):e022576. doi: 10.1161/JAHA.121.022576. Epub 2021 Dec 20. J Am Heart Assoc. 2022. PMID: 34927450 Free PMC article.

3

[Prevalence of hypertension and risk factors in Uygur population in Kashgar area of Xinjiang Uygur Autonomous Region].

Zhang ZB, Xue ZX, Chen HY, Wang TM, Li YH, Chao XF, Wang G, Luo DM, Wu XJ, Nazibam N, Ayxamgul B, Gulbahar E, Zhou ZY, Sun BS, Wang YZ, Wang M. Zhang ZB, et al. Zhonghua Liu Xing Bing Xue Za Zhi. 2017 Jun 10;38(6):709-714. doi: 10.3760/cma.j.issn.0254-6450.2017.06.004. Zhonghua Liu Xing Bing Xue Za Zhi. 2017. PMID: 28647968 Chinese.

4

The Epidemiological Characteristics of Pulmonary Tuberculosis - Kashgar Prefecture, Xinjiang Uygur Autonomous Region, China, 2011-2020.

Tusun D, Abulimiti M, Mamuti X, Liu Z, Xu D, Li G, Peng X, Abudureyimu T, Zhang L, Zhao Y, Ou X. Tusun D, et al. China CDC Wkly. 2021 Jun 25;3(26):557-561. doi: 10.46234/ccdcw2021.144. China CDC Wkly. 2021. PMID: 34594935 Free PMC article.

5

Evaluating and mitigating bias in machine learning models for cardiovascular disease prediction.

Li F, Wu P, Ong HH, Peterson JF, Wei WQ, Zhao J. Li F, et al. J Biomed Inform. 2023 Feb;138:104294. doi: 10.1016/j.jbi.2023.104294. Epub 2023 Jan 24. J Biomed Inform. 2023. PMID: 36706849 Free article.

6

Machine learning approaches improve risk stratification for secondary cardiovascular disease prevention in multiethnic patients.

Sarraju A, Ward A, Chung S, Li J, Scheinker D, Rodríguez F. Sarraju A, et al. Open Heart. 2021 Oct;8(2):e001802. doi: 10.1136/openhrt-2021-001802. Open Heart. 2021. PMID: 34667093 Free PMC article.

7

Dietary patterns and cardiovascular disease in Greek adults: The Hellenic National Nutrition and Health Survey (HNNHS).

Karageorgou D, Magriplis E, Bakogianni I, Mitsopoulou AV, Dimakopoulos I, Micha R, Michas G, Ntouroupi T, Tsaniklidou SM, Argyri K, Chourdakis M, Panagiotakos DB, Zampelas A; HNNHS Contributors; HNNHS Advisory Committee. Karageorgou D, et al. Nutr Metab Cardiovasc Dis. 2020 Feb 10;30(2):201-213. doi: 10.1016/j.numecd.2019.09.024. Epub 2019 Sep 30. Nutr Metab Cardiovasc Dis. 2020. PMID: 31761547

8

Accordance to the Dietary Approaches to Stop Hypertension diet pattern and cardiovascular disease in a British, population-based cohort.

Jones NRV, Forouhi NG, Khaw KT, Wareham NJ, Monsivais P. Jones NRV, et al. Eur J Epidemiol. 2018 Feb;33(2):235-244. doi: 10.1007/s10654-017-0354-8. Epub 2018 Jan 9. Eur J Epidemiol. 2018. PMID: 29318403 Free PMC article.

9

Development of machine learning prediction models to explore nutrients predictive of cardiovascular disease using Canadian linked population-based data.

Morgenstern JD, Rosella LC, Costa AP, Anderson LN. Morgenstern JD, et al. Appl Physiol Nutr Metab. 2022 May;47(5):529-546. doi: 10.1139/apnm-2021-0502. Appl Physiol Nutr Metab. 2022. PMID: 35113677 Free article.

10

Logistic regression was as good as machine learning for predicting major chronic diseases.

Nusinovici S, Tham YC, Chak Yan MY, Wei Ting DS, Li J, Sabanayagam C, Wong TY, Cheng CY. Nusinovici S, et al. J Clin Epidemiol. 2020 Jun;122:56-69. doi: 10.1016/j.jclinepi.2020.03.002. Epub 2020 Mar 10. J Clin Epidemiol. 2020. PMID: 32169597

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