98 related articles for article (PubMed ID: 34487556)
1. Stratifying the Risk of Cardiovascular Disease in Obstructive Sleep Apnea Using Machine Learning.
Gourishetti SC; Taylor R; Isaiah A
Laryngoscope; 2022 Jan; 132(1):234-241. PubMed ID: 34487556
[TBL] [Abstract][Full Text] [Related]
2. Undiagnosed obstructive sleep apnea increases risk of hospitalization among a racially diverse group of older adults with comorbid cardiovascular disease.
Kirk J; Wickwire EM; Somers VK; Johnson DA; Albrecht JS
J Clin Sleep Med; 2023 Jul; 19(7):1175-1181. PubMed ID: 36803353
[TBL] [Abstract][Full Text] [Related]
3. Machine learning model for cardiovascular disease prediction in patients with chronic kidney disease.
Zhu H; Qiao S; Zhao D; Wang K; Wang B; Niu Y; Shang S; Dong Z; Zhang W; Zheng Y; Chen X
Front Endocrinol (Lausanne); 2024; 15():1390729. PubMed ID: 38863928
[TBL] [Abstract][Full Text] [Related]
4. Achieving Better Understanding of Obstructive Sleep Apnea Treatment Effects on Cardiovascular Disease Outcomes through Machine Learning Approaches: A Narrative Review.
Cohen O; Kundel V; Robson P; Al-Taie Z; Suárez-Fariñas M; Shah NA
J Clin Med; 2024 Feb; 13(5):. PubMed ID: 38592223
[TBL] [Abstract][Full Text] [Related]
5. The potential interaction between chemosensitivity and the development of cardiovascular disease in obstructive sleep apnea.
Dai L; Guo J; Hui X; Wang X; Luo J; Huang R; Xiao Y
Sleep Med; 2024 Feb; 114():266-271. PubMed ID: 38244464
[TBL] [Abstract][Full Text] [Related]
6. Integrating Phenotypic Information of Obstructive Sleep Apnea and Deep Representation of Sleep-Event Sequences for Cardiovascular Risk Prediction.
Zheng Y; Song Z; Cheng B; Peng X; Huang Y; Min M
Res Sq; 2024 Mar; ():. PubMed ID: 38559110
[TBL] [Abstract][Full Text] [Related]
7. Risk-prediction model for incident hypertension in patients with obstructive sleep apnea based on SpO2 signals.
You J; Li J; Li X; Li H; Tu J; Zhang Y; Gao J; Wu J; Ye J
Annu Int Conf IEEE Eng Med Biol Soc; 2023 Jul; 2023():1-4. PubMed ID: 38083398
[TBL] [Abstract][Full Text] [Related]
8. Exploring machine learning strategies for predicting cardiovascular disease risk factors from multi-omic data.
Drouard G; Mykkänen J; Heiskanen J; Pohjonen J; Ruohonen S; Pahkala K; Lehtimäki T; Wang X; Ollikainen M; Ripatti S; Pirinen M; Raitakari O; Kaprio J
BMC Med Inform Decis Mak; 2024 May; 24(1):116. PubMed ID: 38698395
[TBL] [Abstract][Full Text] [Related]
9. Determination of the Incidence of Cardiovascular Composite Events in Patients with Obstructive Sleep Apnea: A 3-year follow-up Study.
ARYA Atheroscler; 2023 Jan; 19(1):53-60. PubMed ID: 38883153
[TBL] [Abstract][Full Text] [Related]
10. Increased Levels of VCAM-1 in Patients with High Cardiovascular Risk and Obstructive Sleep Apnea Syndrome.
Chetan IM; Vesa ȘC; Domokos Gergely B; Beyer RS; Tomoaia R; Cabau G; Vulturar DM; Pop D; Todea D
Biomedicines; 2023 Dec; 12(1):. PubMed ID: 38255155
[TBL] [Abstract][Full Text] [Related]
11. Development of machine learning-based models to predict 10-year risk of cardiovascular disease: a prospective cohort study.
You J; Guo Y; Kang JJ; Wang HF; Yang M; Feng JF; Yu JT; Cheng W
Stroke Vasc Neurol; 2023 Dec; 8(6):475-485. PubMed ID: 37105576
[TBL] [Abstract][Full Text] [Related]
12. New insights from integrated bioinformatics analysis: the role of circadian rhythm disruption and immune infiltration in obstructive sleep apnea disease.
Zhang X; Wang Y; Pan Z; Hu K
Front Immunol; 2023; 14():1273114. PubMed ID: 38169659
[TBL] [Abstract][Full Text] [Related]
13. Circulating markers of oxidative stress and risk of incident cardiovascular events in obstructive sleep apnea.
Allen AJH; Peres BU; Liu Y; Jen R; Shah A; Laher I; Almeida F; Taylor C; Ghafoor AA; Ayas NT
Sleep Biol Rhythms; 2022 Oct; 20(4):533-540. PubMed ID: 38468626
[TBL] [Abstract][Full Text] [Related]
14. Study of cardiovascular disease prediction model based on random forest in eastern China.
Yang L; Wu H; Jin X; Zheng P; Hu S; Xu X; Yu W; Yan J
Sci Rep; 2020 Mar; 10(1):5245. PubMed ID: 32251324
[TBL] [Abstract][Full Text] [Related]
15. Prediction model for cardiovascular disease in patients with diabetes using machine learning derived and validated in two independent Korean cohorts.
Sang H; Lee H; Lee M; Park J; Kim S; Woo HG; Rahmati M; Koyanagi A; Smith L; Lee S; Hwang YC; Park TS; Lim H; Yon DK; Rhee SY
Sci Rep; 2024 Jun; 14(1):14966. PubMed ID: 38942775
[TBL] [Abstract][Full Text] [Related]
16. Characterisation of Symptom and Polysomnographic Profiles Associated with Cardiovascular Risk in a Sleep Clinic Population with Obstructive Sleep Apnoea.
Kemp E; Sutherland K; Bin YS; Chan ASL; Dissanayake H; Yee BJ; Kairaitis K; Wheatley JR; de Chazal P; Piper AJ; Cistulli PA;
Nat Sci Sleep; 2024; 16():461-471. PubMed ID: 38737461
[TBL] [Abstract][Full Text] [Related]
17. Multidimensional Sleep and Mortality in Older Adults: A Machine-Learning Comparison With Other Risk Factors.
Wallace ML; Buysse DJ; Redline S; Stone KL; Ensrud K; Leng Y; Ancoli-Israel S; Hall MH
J Gerontol A Biol Sci Med Sci; 2019 Nov; 74(12):1903-1909. PubMed ID: 30778527
[TBL] [Abstract][Full Text] [Related]
18. Risk stratification in very old adults: how to best gauge risk as the basis of management choices for patients aged over 80.
Bell SP; Saraf A
Prog Cardiovasc Dis; 2014; 57(2):197-203. PubMed ID: 25216619
[TBL] [Abstract][Full Text] [Related]
19. Emerging role of machine learning in cardiovascular disease investigation and translations.
Stevens BR; Pepine CJ
Am Heart J Plus; 2021 Nov; 11():100050. PubMed ID: 38559318
[TBL] [Abstract][Full Text] [Related]
20. We Can Use Machine Learning to Predict Obstructive Sleep Apnea.
Schwab RJ; Erus G
Am J Respir Crit Care Med; 2024 May; ():. PubMed ID: 38701391
[No Abstract] [Full Text] [Related]
[Next] [New Search]