Abstract
As reported by the economic survey 2019–20, the medical infrastructure evidenced the shortage of doctors in India. The ratio of doctor–patient in India is 1:1456 against the recommendation of 1:1000 by the World Health Organization (WHO). This paper proposes a prototype of an automated and intelligent low-cost heart monitoring system to bridge the gap between doctor and patient. The model uses machine learning techniques for decision-making and is deployed in an interactive user interface. Additionally, the user experience is also deployed in the IoT cloud platform for tracing the health record of an individual and notifies users about their health status. Further, the proposed model is intended to outperform the existing models using prescriptive analytics. Thus, it provides a visionary approach by rapidly detecting trends and making recommendations on behalf of manual medical supervision.
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Tiwari, K., Ansari, S., Kushwaha, G. (2023). Earlier Heart Disease Prediction System Using Machine Learning. In: Shukla, P.K., Singh, K.P., Tripathi, A.K., Engelbrecht, A. (eds) Computer Vision and Robotics. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-19-7892-0_16
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