Key result
AI and ML show potential to automate valvular heart disease care via improved imaging and prediction.
Why the study?
Big data and supercomputing have advanced artificial intelligence, creating opportunities to enhance diagnosis and clinical decision-making in valvular heart diseases.
AI technologies, including machine learning and deep learning, show significant potential in automating and improving the accuracy of diagnosing and managing valvular heart diseases through auscultation and imaging analysis.
Should not yet change valvular heart disease practice; leaves open need for prospective validation trials.
Artificial intelligence (AI) is gradually changing every aspect of social life, and healthcare is no exception. The clinical procedures that were supposed to, and could previously only be handled by human experts can now be carried out by machines in a more accurate and efficient way. The coming era of big data and the advent of supercomputers provides great opportunities to the development of AI technology for the enhancement of diagnosis and clinical decision-making. This review provides an introduction to AI and highlights its applications in the clinical flow of diagnosing and treating valvular heart diseases (VHDs). More specifically, this review first introduces some key concepts and subareas in AI. Secondly, it discusses the application of AI in heart sound auscultation and medical image analysis for assistance in diagnosing VHDs. Thirdly, it introduces using AI algorithms to identify risk factors and predict mortality of cardiac surgery. This review also describes the state-of-the-art autonomous surgical robots and their roles in cardiac surgery and intervention.
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Long et al. (2020) conducted a review in Valvular heart diseases. Artificial intelligence was evaluated. Artificial intelligence and machine learning algorithms demonstrate significant potential in automating the diagnosis and treatment of valvular heart diseases through improved image analysis and risk prediction.
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