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T, Vora; Pendyala, Prashant; Schunneman, Holger; López‐Candales, Angel

doi:10.1097/00019501-200305000-00007

Cited by 1 publication

(3 citation statements)

References 14 publications

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“…1G ). Overall, these results demonstrate the ability to induce cardiovascular stress and acute myocardial ischemia, with observed physiological feature changes similar to human myocardial ischemia ( 4 , 8 , 10 , 11 , 31 , 32 , 41 , 42 ).…”

Section: Resultssupporting

confidence: 55%

“…1C ) ( 40 ), and corrected QT (QTc) prolongation (using Bazett’s formula; an electrophysiological abnormality occurring during acute myocardial ischemia, related to proarrhythmic states; Fig. 1D ) ( 41 , 42 ). The combined D + NE infusion tended to have the largest effect.…”

Section: Resultsmentioning

confidence: 99%

“…2) Related to Fig. 1D : QTc across time was not a component of the overall 13-element feature vector but was calculated offline using the emka ecgAUTO software and Bazett’s formula [similar to previous studies ( 41 , 42 )]: QTc = (QT interval; milliseconds)/√ (RR interval; milliseconds).…”

Section: Methodsmentioning

confidence: 99%

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Dynamic detection and reversal of myocardial ischemia using an artificially intelligent bioelectronic medicine

et al. 2022

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Myocardial ischemia is spontaneous, frequently asymptomatic, and contributes to fatal cardiovascular consequences. Importantly, myocardial sensory networks cannot reliably detect and correct myocardial ischemia on their own. Here, we demonstrate an artificially intelligent and responsive bioelectronic medicine, where an artificial neural network (ANN) supplements myocardial sensory networks, enabling reliable detection and correction of myocardial ischemia. ANNs were first trained to decode spontaneous cardiovascular stress and myocardial ischemia with an overall accuracy of ~92%. ANN-controlled vagus nerve stimulation (VNS) significantly mitigated major physiological features of myocardial ischemia, including ST depression and arrhythmias. In contrast, open-loop VNS or ANN-controlled VNS following a caudal vagotomy essentially failed to reverse cardiovascular pathophysiology. Last, variants of ANNs were used to meet clinically relevant needs, including interpretable visualizations and unsupervised detection of emerging cardiovascular stress. Overall, these preclinical results suggest that ANNs can potentially supplement deficient myocardial sensory networks via an artificially intelligent bioelectronic medicine system.

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