Analysis of the mechanism of antipsychotics induced abnormal ECG using Medical Ontologies and Medical Knowledge Graphs

Objective: Our aim is to understand the underlying mechanisms of antipsychotics-induced ECG abnormalities by using artificial intelligence (AI) method and information processing technique. Methods: This study employed the SNOMED CT (Systematized Nomenclature of Medicine - Clinical Terms) and the knowledge graph of brain science, to find relevant concepts associated with ECG abnormalities and antipsychotics usage. Results: Approximately 30 relevant publications were found, only 10 articles were included in this comprehensive analysis study. Our findings suggest that the underlying mechanisms of antipsychotic-induced ECG abnormalities include immediate, medium and lasting effects on the predisposing level, the autonomic nervous system, cardiomyocytes, and the blood vessel levels. Conclusions: The potential mechanisms underpinning antipsychotics-induced ECG abnormalities include predisposing, the autonomic nervous system, cardiomyocytes, and the blood vessel levels by use of the NOMED CT and the knowledge graph of brain science.