BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

144 related articles for article (PubMed ID: 36247412)

  • 1. Real-world performance, long-term efficacy, and absence of bias in the artificial intelligence enhanced electrocardiogram to detect left ventricular systolic dysfunction.
    Harmon DM; Carter RE; Cohen-Shelly M; Svatikova A; Adedinsewo DA; Noseworthy PA; Kapa S; Lopez-Jimenez F; Friedman PA; Attia ZI
    Eur Heart J Digit Health; 2022 Jun; 3(2):238-244. PubMed ID: 36247412
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Assessing and Mitigating Bias in Medical Artificial Intelligence: The Effects of Race and Ethnicity on a Deep Learning Model for ECG Analysis.
    Noseworthy PA; Attia ZI; Brewer LC; Hayes SN; Yao X; Kapa S; Friedman PA; Lopez-Jimenez F
    Circ Arrhythm Electrophysiol; 2020 Mar; 13(3):e007988. PubMed ID: 32064914
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Artificial Intelligence-Enabled ECG Algorithm to Identify Patients With Left Ventricular Systolic Dysfunction Presenting to the Emergency Department With Dyspnea.
    Adedinsewo D; Carter RE; Attia Z; Johnson P; Kashou AH; Dugan JL; Albus M; Sheele JM; Bellolio F; Friedman PA; Lopez-Jimenez F; Noseworthy PA
    Circ Arrhythm Electrophysiol; 2020 Aug; 13(8):e008437. PubMed ID: 32986471
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Postdevelopment Performance and Validation of the Artificial Intelligence-Enhanced Electrocardiogram for Detection of Cardiac Amyloidosis.
    Harmon DM; Mangold K; Suarez AB; Scott CG; Murphree DH; Malik A; Attia ZI; Lopez-Jimenez F; Friedman PA; Dispenzieri A; Grogan M
    JACC Adv; 2023 Oct; 2(8):. PubMed ID: 38638999
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Artificial intelligence-enabled electrocardiogram screens low left ventricular ejection fraction with a degree of confidence.
    Lee CH; Liu WT; Lou YS; Lin CS; Fang WH; Lee CC; Ho CL; Wang CH; Lin C
    Digit Health; 2022; 8():20552076221143249. PubMed ID: 36532114
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Left ventricular systolic dysfunction identification using artificial intelligence-augmented electrocardiogram in cardiac intensive care unit patients.
    Jentzer JC; Kashou AH; Attia ZI; Lopez-Jimenez F; Kapa S; Friedman PA; Noseworthy PA
    Int J Cardiol; 2021 Mar; 326():114-123. PubMed ID: 33152415
    [TBL] [Abstract][Full Text] [Related]  

  • 7. External validation of a deep learning electrocardiogram algorithm to detect ventricular dysfunction.
    Attia IZ; Tseng AS; Benavente ED; Medina-Inojosa JR; Clark TG; Malyutina S; Kapa S; Schirmer H; Kudryavtsev AV; Noseworthy PA; Carter RE; Ryabikov A; Perel P; Friedman PA; Leon DA; Lopez-Jimenez F
    Int J Cardiol; 2021 Apr; 329():130-135. PubMed ID: 33400971
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Prospective validation of a deep learning electrocardiogram algorithm for the detection of left ventricular systolic dysfunction.
    Attia ZI; Kapa S; Yao X; Lopez-Jimenez F; Mohan TL; Pellikka PA; Carter RE; Shah ND; Friedman PA; Noseworthy PA
    J Cardiovasc Electrophysiol; 2019 May; 30(5):668-674. PubMed ID: 30821035
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Artificial Intelligence-Enabled Electrocardiogram Predicted Left Ventricle Diameter as an Independent Risk Factor of Long-Term Cardiovascular Outcome in Patients With Normal Ejection Fraction.
    Chen HY; Lin CS; Fang WH; Lee CC; Ho CL; Wang CH; Lin C
    Front Med (Lausanne); 2022; 9():870523. PubMed ID: 35479951
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Left ventricular systolic dysfunction predicted by artificial intelligence using the electrocardiogram in Chagas disease patients-The SaMi-Trop cohort.
    Brito BOF; Attia ZI; Martins LNA; Perel P; Nunes MCP; Sabino EC; Cardoso CS; Ferreira AM; Gomes PR; Luiz Pinho Ribeiro A; Lopez-Jimenez F
    PLoS Negl Trop Dis; 2021 Dec; 15(12):e0009974. PubMed ID: 34871321
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Artificial intelligence-based identification of left ventricular systolic dysfunction from 12-lead electrocardiograms: external validation and advanced application of an existing model.
    König S; Hohenstein S; Nitsche A; Pellissier V; Leiner J; Stellmacher L; Hindricks G; Bollmann A
    Eur Heart J Digit Health; 2024 Mar; 5(2):144-151. PubMed ID: 38505486
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Community-based participatory research application of an artificial intelligence-enhanced electrocardiogram for cardiovascular disease screening: A FAITH! Trial ancillary study.
    Harmon DM; Adedinsewo D; Van't Hof JR; Johnson M; Hayes SN; Lopez-Jimenez F; Jones C; Attia ZI; Friedman PA; Patten CA; Cooper LA; Brewer LC
    Am J Prev Cardiol; 2022 Dec; 12():100431. PubMed ID: 36419480
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Development and Validation of a Deep-Learning Model to Screen for Hyperkalemia From the Electrocardiogram.
    Galloway CD; Valys AV; Shreibati JB; Treiman DL; Petterson FL; Gundotra VP; Albert DE; Attia ZI; Carter RE; Asirvatham SJ; Ackerman MJ; Noseworthy PA; Dillon JJ; Friedman PA
    JAMA Cardiol; 2019 May; 4(5):428-436. PubMed ID: 30942845
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Electrocardiogram-Artificial Intelligence and Immune-Mediated Necrotizing Myopathy: Predicting Left Ventricular Dysfunction and Clinical Outcomes.
    Klein CJ; Ozcan I; Attia ZI; Cohen-Shelly M; Lerman A; Medina-Inojosa JR; Lopez-Jimenez F; Friedman PA; Milone M; Shelly S
    Mayo Clin Proc Innov Qual Outcomes; 2022 Oct; 6(5):450-457. PubMed ID: 36147867
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Automated detection of low ejection fraction from a one-lead electrocardiogram: application of an AI algorithm to an electrocardiogram-enabled Digital Stethoscope
    Attia ZI; Dugan J; Rideout A; Maidens JN; Venkatraman S; Guo L; Noseworthy PA; Pellikka PA; Pham SL; Kapa S; Friedman PA; Lopez-Jimenez F
    Eur Heart J Digit Health; 2022 Sep; 3(3):373-379. PubMed ID: 36712160
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Importance of external validation and subgroup analysis of artificial intelligence in the detection of low ejection fraction from electrocardiograms.
    Yagi R; Goto S; Katsumata Y; MacRae CA; Deo RC
    Eur Heart J Digit Health; 2022 Dec; 3(4):654-657. PubMed ID: 36710903
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Spectrum bias in algorithms derived by artificial intelligence: a case study in detecting aortic stenosis using electrocardiograms.
    Tseng AS; Shelly-Cohen M; Attia IZ; Noseworthy PA; Friedman PA; Oh JK; Lopez-Jimenez F
    Eur Heart J Digit Health; 2021 Dec; 2(4):561-567. PubMed ID: 36713099
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A comprehensive artificial intelligence-enabled electrocardiogram interpretation program.
    Kashou AH; Ko WY; Attia ZI; Cohen MS; Friedman PA; Noseworthy PA
    Cardiovasc Digit Health J; 2020; 1(2):62-70. PubMed ID: 35265877
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Mortality Prediction in Cardiac Intensive Care Unit Patients: A Systematic Review of Existing and Artificial Intelligence Augmented Approaches.
    Rafie N; Jentzer JC; Noseworthy PA; Kashou AH
    Front Artif Intell; 2022; 5():876007. PubMed ID: 35711617
    [TBL] [Abstract][Full Text] [Related]  

  • 20. An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction.
    Attia ZI; Noseworthy PA; Lopez-Jimenez F; Asirvatham SJ; Deshmukh AJ; Gersh BJ; Carter RE; Yao X; Rabinstein AA; Erickson BJ; Kapa S; Friedman PA
    Lancet; 2019 Sep; 394(10201):861-867. PubMed ID: 31378392
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.