From Diagnosis to Management: Unveiling the Challenges of Artificial Intelligence Solutions in Cardiovascular Healthcare

Abstract Cardiovascular diseases (CVDs) are the leading cause of mortality in the world. Artificial Intelligence (AI) offers an opportunity to improve the quality of care provided to cardiovascular patients due to its ability to handle large and complex data. Despite promising results obtained in several studies, widespread adoption of AI in cardiovascular care is lacking due to the existence of some gaps. The goal of this study is to analyze the existing challenges faced by AI solutions in cardiovascular care. This study adopted a mixed-methods research approach, combining semi-structured interviews with responses from a self-administered online survey. A total of 5 interviews were conducted and 91 valid survey responses were obtained. Survey respondents included doctors, nurses, medical researchers, health I specialists, hospital administrators, and other clinically affiliated participants working with cardiovascular patients. Participants identified 8 major challenges: data-related challenges, regulatory challenges, infrastructural challenges, gaps in knowledge, transparency challenges, ethical challenges, issues with change management, and acceptance challenges. These gaps hinder the adoption of AI in cardiovascular care and taking proactive measures to address these challenges is key to fostering AI adoption.