Mapping of Neuro-Cardiac Electrophysiology: Interlinking Epilepsy and Arrhythmia.
Sidhartha G SenapatiAditi K BhanushaliSimmy LahoriMridula Sree NaagendranShreya SriramArghyadeep GangulyMounika PusaDevanshi N DamaniKanchan KulkarniShivaram P ArunachalamPublished in: Journal of cardiovascular development and disease (2023)
The interplay between neurology and cardiology has gained significant attention in recent years, particularly regarding the shared pathophysiological mechanisms and clinical comorbidities observed in epilepsy and arrhythmias. Neuro-cardiac electrophysiology mapping involves the comprehensive assessment of both neural and cardiac electrical activity, aiming to unravel the intricate connections and potential cross-talk between the brain and the heart. The emergence of artificial intelligence (AI) has revolutionized the field by enabling the analysis of large-scale data sets, complex signal processing, and predictive modeling. AI algorithms have been applied to neuroimaging, electroencephalography (EEG), electrocardiography (ECG), and other diagnostic modalities to identify subtle patterns, classify disease subtypes, predict outcomes, and guide personalized treatment strategies. In this review, we highlight the potential clinical implications of neuro-cardiac mapping and AI in the management of epilepsy and arrhythmias. We address the challenges and limitations associated with these approaches, including data quality, interpretability, and ethical considerations. Further research and collaboration between neurologists, cardiologists, and AI experts are needed to fully unlock the potential of this interdisciplinary field.
Keyphrases
- artificial intelligence
- big data
- machine learning
- deep learning
- left ventricular
- high resolution
- high density
- electronic health record
- human health
- risk assessment
- resting state
- congenital heart disease
- type diabetes
- metabolic syndrome
- cardiac surgery
- quality improvement
- adipose tissue
- heart rate variability
- climate change
- heart rate
- skeletal muscle
- multiple sclerosis
- insulin resistance
- glycemic control