293 related articles for article (PubMed ID: 34343838)
1. Machine-Learning-Derived Model for the Stratification of Cardiovascular risk in Patients with Ischemic Stroke.
Ntaios G; Sagris D; Kallipolitis A; Karagkiozi E; Korompoki E; Manios E; Plagianakos V; Vemmos K; Maglogiannis I
J Stroke Cerebrovasc Dis; 2021 Oct; 30(10):106018. PubMed ID: 34343838
[TBL] [Abstract][Full Text] [Related]
2. Comparative Effectiveness of Machine Learning Approaches for Predicting Gastrointestinal Bleeds in Patients Receiving Antithrombotic Treatment.
Herrin J; Abraham NS; Yao X; Noseworthy PA; Inselman J; Shah ND; Ngufor C
JAMA Netw Open; 2021 May; 4(5):e2110703. PubMed ID: 34019087
[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. Prediction of Hidden Coronary Artery Disease Using Machine Learning in Patients With Acute Ischemic Stroke.
Heo J; Yoo J; Lee H; Lee IH; Kim JS; Park E; Kim YD; Nam HS
Neurology; 2022 Jul; 99(1):e55-e65. PubMed ID: 35470135
[TBL] [Abstract][Full Text] [Related]
5. Multiclass machine learning vs. conventional calculators for stroke/CVD risk assessment using carotid plaque predictors with coronary angiography scores as gold standard: a 500 participants study.
Jamthikar AD; Gupta D; Mantella LE; Saba L; Laird JR; Johri AM; Suri JS
Int J Cardiovasc Imaging; 2021 Apr; 37(4):1171-1187. PubMed ID: 33184741
[TBL] [Abstract][Full Text] [Related]
6. Extreme Gradient Boosting Model Has a Better Performance in Predicting the Risk of 90-Day Readmissions in Patients with Ischaemic Stroke.
Xu Y; Yang X; Huang H; Peng C; Ge Y; Wu H; Wang J; Xiong G; Yi Y
J Stroke Cerebrovasc Dis; 2019 Dec; 28(12):104441. PubMed ID: 31627995
[TBL] [Abstract][Full Text] [Related]
7. Development and Validation of Machine Learning Algorithms to Predict 1-Year Ischemic Stroke and Bleeding Events in Patients with Atrial Fibrillation and Cancer.
Truong B; Zheng J; Hornsby L; Fox B; Chou C; Qian J
Cardiovasc Toxicol; 2024 Apr; 24(4):365-374. PubMed ID: 38499940
[TBL] [Abstract][Full Text] [Related]
8. Development and Validation of a Risk Score Model for Predicting the Cardiovascular Outcomes After Breast Cancer Therapy: The CHEMO-RADIAT Score.
Kim DY; Park MS; Youn JC; Lee S; Choi JH; Jung MH; Kim LS; Kim SH; Han S; Ryu KH
J Am Heart Assoc; 2021 Aug; 10(16):e021931. PubMed ID: 34369199
[TBL] [Abstract][Full Text] [Related]
9. Leveraging Machine Learning Techniques to Forecast Patient Prognosis After Percutaneous Coronary Intervention.
Zack CJ; Senecal C; Kinar Y; Metzger Y; Bar-Sinai Y; Widmer RJ; Lennon R; Singh M; Bell MR; Lerman A; Gulati R
JACC Cardiovasc Interv; 2019 Jul; 12(14):1304-1311. PubMed ID: 31255564
[TBL] [Abstract][Full Text] [Related]
10. Comparison of Risk Scores for the Prediction of the Overall Cardiovascular Risk in Patients with Ischemic Stroke: The Athens Stroke Registry.
Georgiopoulos G; Ntaios G; Stamatelopoulos K; Manios E; Korompoki E; Vemmou E; Milionis H; Masi S; Lip GYH; Vemmos K
J Stroke Cerebrovasc Dis; 2019 Dec; 28(12):104415. PubMed ID: 31669071
[TBL] [Abstract][Full Text] [Related]
11. Maximization of the usage of coronary CTA derived plaque information using a machine learning based algorithm to improve risk stratification; insights from the CONFIRM registry.
van Rosendael AR; Maliakal G; Kolli KK; Beecy A; Al'Aref SJ; Dwivedi A; Singh G; Panday M; Kumar A; Ma X; Achenbach S; Al-Mallah MH; Andreini D; Bax JJ; Berman DS; Budoff MJ; Cademartiri F; Callister TQ; Chang HJ; Chinnaiyan K; Chow BJW; Cury RC; DeLago A; Feuchtner G; Hadamitzky M; Hausleiter J; Kaufmann PA; Kim YJ; Leipsic JA; Maffei E; Marques H; Pontone G; Raff GL; Rubinshtein R; Shaw LJ; Villines TC; Gransar H; Lu Y; Jones EC; Peña JM; Lin FY; Min JK
J Cardiovasc Comput Tomogr; 2018; 12(3):204-209. PubMed ID: 29753765
[TBL] [Abstract][Full Text] [Related]
12. A data-driven approach to predicting diabetes and cardiovascular disease with machine learning.
Dinh A; Miertschin S; Young A; Mohanty SD
BMC Med Inform Decis Mak; 2019 Nov; 19(1):211. PubMed ID: 31694707
[TBL] [Abstract][Full Text] [Related]
13. Development and Internal Validation of Machine Learning Algorithms for Preoperative Survival Prediction of Extremity Metastatic Disease.
Thio QCBS; Karhade AV; Bindels BJJ; Ogink PT; Bramer JAM; Ferrone ML; Calderón SL; Raskin KA; Schwab JH
Clin Orthop Relat Res; 2020 Feb; 478(2):322-333. PubMed ID: 31651589
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. Atrial Fibrillation Burden Signature and Near-Term Prediction of Stroke: A Machine Learning Analysis.
Han L; Askari M; Altman RB; Schmitt SK; Fan J; Bentley JP; Narayan SM; Turakhia MP
Circ Cardiovasc Qual Outcomes; 2019 Oct; 12(10):e005595. PubMed ID: 31610712
[TBL] [Abstract][Full Text] [Related]
16. Prediction of Clinical Outcome in Patients with Large-Vessel Acute Ischemic Stroke: Performance of Machine Learning versus SPAN-100.
Jiang B; Zhu G; Xie Y; Heit JJ; Chen H; Li Y; Ding V; Eskandari A; Michel P; Zaharchuk G; Wintermark M
AJNR Am J Neuroradiol; 2021 Jan; 42(2):240-246. PubMed ID: 33414230
[TBL] [Abstract][Full Text] [Related]
17. Machine learning assessment of myocardial ischemia using angiography: Development and retrospective validation.
Hae H; Kang SJ; Kim WJ; Choi SY; Lee JG; Bae Y; Cho H; Yang DH; Kang JW; Lim TH; Lee CH; Kang DY; Lee PH; Ahn JM; Park DW; Lee SW; Kim YH; Lee CW; Park SW; Park SJ
PLoS Med; 2018 Nov; 15(11):e1002693. PubMed ID: 30422987
[TBL] [Abstract][Full Text] [Related]
18. Using machine learning to predict stroke-associated pneumonia in Chinese acute ischaemic stroke patients.
Li X; Wu M; Sun C; Zhao Z; Wang F; Zheng X; Ge W; Zhou J; Zou J
Eur J Neurol; 2020 Aug; 27(8):1656-1663. PubMed ID: 32374076
[TBL] [Abstract][Full Text] [Related]
19. Prediction of Persistent Impaired Glucose Tolerance in Patients with Minor Ischemic Stroke or Transient Ischemic Attack.
Osei E; den Hertog HM; Fonville S; Brouwers PJAM; Mulder LJMM; Koudstaal PJ; Dippel DWJ; Zandbergen AAM; Lingsma HF
J Stroke Cerebrovasc Dis; 2020 Jun; 29(6):104815. PubMed ID: 32303400
[TBL] [Abstract][Full Text] [Related]
20. Automated Prediction of Proximal Middle Cerebral Artery Occlusions in Noncontrast Brain Computed Tomography.
Kim PE; Yang H; Kim D; Sunwoo L; Kim CK; Kim BJ; Kim JT; Ryu WS; Kim HS
Stroke; 2024 Jun; 55(6):1609-1618. PubMed ID: 38787932
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
