Revolutionizing Cardiovascular Devices: AI, Machine Learning, conversational AI and Deep Learning in Healthcare, Cybersecurity, and Aerodynamics
Keywords:
Artificial intelligence, big data, machine learning, deep learning, cardiovascular devices, real-time monitoring, predictive analysis, Conversational Ai, security threat, fluid dynamics, device fabrication, patient treatment.Abstract
AI, ML, and DL have played a major role in enhancing and improving cardiovascular devices leading to more effective treatment methods, tailored treatment, and thus more precise. This paper aims to discuss the ways in which AI and ML improve design, efficiency and reliability of cardiovascular equipment such as pumps, stents, valves, and wearable monitoring devices. Also aerobic activity enhanced by AI and catering to blood flow dynamics and heart rhythms thereby enhancing patient health. One example is a chatbot – Chatgpt, which can provide more precise real-time information, help to make decisions or explain the information provided to patients. Similarly, cybersecurity initiatives work well to deal with risks which arise from artificial intelligence in medical instruments. Cardiovascular diseases have benefited from these advances with wearables and remote monitoring systems using artificial intelligence. Nevertheless, the incorporation of AI into cardiovascular healthcare has come with problems like data privacy and compliance that are foreseeable to hinder the implementation of AI in cardiovascular healthcare in the future; on the same note, this incorporation has the potential to transform a cardiovascular healthcare setting, providing an efficient and patients’ focused procedure in the end.
