MUMBAI, India, Aug. 31 -- Intellectual Property India has published a patent application (202641100116 A) filed by Karpagam College Of Engineering; Karpagam Academy Of Higher Education; Dr A Rajendran; and Annushiya K on August 19, 2026, for Heartsync Pro: Temporal Cardiovascular Risk Prediction Using Explainable Machine Learning And Risk Progression Index.
Inventors include Dr A Rajendran; and Annushiya K.
The application for the patent was published on August 28, 2026, under issue no. 35/2026.
Abstract: Cardiovascular diseases, or CVDs cause of mortality worldwide, emphasizing the need for early diagnosis, constant monitoring, and individual interventions. Although a variety of machine learning methods has been broadly adopted for the prediction of heart diseases, most existing systems provide static, one-time risk assessment without explanation contributing factors or tracking changes over time. This paper suggests a rigorous framework called HeartSync Pro in which cardiovascular risk prediction and monitoring take place. It combines explainable machine learning with temporal risk analysis. Logistic Regression is used for probabilistic disease prediction due to its interpretability, while Random Forest is used for computing feature importance. Forest also points out the dominant clinical contributors. In addition, there exists a new version of CRFs that considers local context A new metric, designated as ’Risk Progression Index’ (RPI), may be devised to quantify variations in cardiovascular risk, enabling the early diagnosis of accelerating risk trends. Experimental evaluation shows that the model can reach an accuracy of 79%, F1 Score of 81%. An AUC of 0.87,validating the effectiveness of it in supporting Proactive clinical decision-making.
Disclaimer: Curated by HT Syndication.
