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    Beyond MELD Score: Association of Machine Learning-derived CT Body Composition with 90-Day Mortality Post Transjugular Intrahepatic Portosystemic Shunt Placement by Elhakim, Tarig, Mansur, Arian, Kondo, Jordan, Omar, Omar M. F., Ahmed, Khalid, Tabari, Azadeh, Brea, Allison, Ndakwah, Gabriel, Iqbal, Shams, Allegretti, Andrew S., Fintelmann, Florian J., Wehrenberg-Klee, Eric, Bridge, Christopher, Daye, Dania

    Published 2024
    “…Multivariable logistic regression showed that SMA (OR = 0.97, p < 0.01), SMI (OR = 0.94, p = 0.03), SFA (OR = 0.99, p = 0.01), and VFA (OR = 0.99, p = 0.02) remained significant predictors of 90-day mortality when adjusted for MELD score. ROC curve analysis demonstrated that including SMA, SFA, and VFA improves the predictive power of MELD score in predicting 90-day mortality after TIPS (AUC, 0.84; 95% CI: 0.77, 0.91; p = 0.02). …”
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    Heart failure risk stratification using artificial intelligence applied to electrocardiogram images: a multinational study by Dhingra, LS, Aminorroaya, A, Sangha, V, Pedroso, AF, Asselbergs, FW, Brant, LCC, Barreto, SM, Ribeiro, ALP, Krumholz, HM, Oikonomou, EK, Khera, R

    Published 2025
    “…Model discrimination was 0.718 in YNHHS, 0.769 in UKB, and 0.810 in ELSA-Brasil. In YNHHS and ELSA-Brasil, incorporating AI-ECG with PCP-HF yielded a significant improvement in discrimination over PCP-HF alone. …”
    Journal article
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