MaxYield™️ White Paper
"Identifying true P and QRS complexes after noise and artefact are removed would substantially increase the probability that a true critical abnormality is captured (sensitivity), while also limiting false positives—which are often detected by Technicians but are time-consuming, fatiguing, and lead to ‘alarm fatigue.’ It also allows diagnosis of not only pauses but their nature (e.g., second degree AV block, 3rd° AV block, or sinus pauses), as well as differentiation of SVT from VT."
Dr. Paul Dorian
Cardiologist
MaxYield™️: AI-Powered Precision in ECG Labeling
Holter monitors and long-term ECG recordings can capture millions of heartbeats, but current software tools often struggle with noise and variability, leaving technicians to manually adjust and review waveforms. NeuralCloud’s MaxYield™️ addresses this challenge by applying a neural network to accurately detect P-wave, QRS complex, and T-wave onsets and offsets, even in noisy signals.
In a validation study comparing MaxYield™️ to 15 certified cardiology technologists, the algorithm ranked second overall - outperformed only by the top human expert. MaxYield™️ not only matched expert-level accuracy but also demonstrated superior consistency (low error and tight interquartile ranges), critical for scalable, reliable ECG analysis. By processing extended ECG files (up to 14.5 days) with high fidelity, MaxYield™️ significantly enhances the ability to detect paroxysmal arrhythmias, streamlines technician workflow, and supports timely, accurate diagnosis.
