Introduction: Cardiac MRI (CMR) is the gold standard for right ventricular function (RVF) because echo assessment is limited. Potential echo parameters to assess RVF include RV fractional area change (FAC), RV free wall strain (FWS), and tricuspid annular plane systolic excursion (TAPSE) on apical 4-chamber (A4C) view. We compared a new Artificial Intelligence method that tracks the RV almost instantaneously in a single 4-chamber view (AI, LVivo RV®, DiA Imaging, Figure) to quantify RVF vs CMR. Methods: We compared AI RVF against CMR in 125 pts. Abnormal LVEF and RVEF were defined as <57% and <49% respectively. Echo closest to CMR date was analyzed with AI RV to obtain FAC, FWS, and TAPSE. We defined abnormal RVF by DiA Imaging’s predetermined thresholds. Sensitivities and specificities for abnormal RVF and chi-square (χ 2 ) tests were calculated for each variable against CMR RVEF. Results: Of the 125 pts, 55 (44%) were female with median age 55 [Q1 44, Q3 67] years. Thirty pts (24%) had abnormal RVEF and 78 (62.4%) had abnormal LVEF by CMR. All pts with abnormal RVEF had abnormal LVEF. Compared to CMR, AI RV sensitivities and specificities for abnormal RVEF were: FAC 87% and 60%, FWS 80% and 61%, TAPSE 77% and 54%, any 2 criteria 83% and 61%, and all 3 criteria 63% and 69%. AI RV χ 2 values were: FAC 19.9 (p<0.001), FWS 15.4 (p<0.001), TAPSE 8.4 (p=0.004), any 2 criteria 18.0 (p<0.001), and all 3 criteria 10.4 (p=0.001). Conclusions: This is the first validation of a novel AI method (LVivo RV®) that can detect RV dysfunction using 3 standard RV measurements from a single A4C view with good sensitivity and specificity compared to volumetric CMR as the gold standard.