Unmasking Heart Disease Deaths: A Predictive Journey in Pakistan’s Sindh Province

Heart disease is a major health concern globally, with its impact growing in many regions. In Pakistan's Sindh province, researchers took on the task of forecasting heart disease deaths from 1999 to 2021 using data from the Nawabshah area's civil hospital. They employed various methods, from simple statistical models like Naïve and Holt-Winters, to more complex ones like the Artificial Neural Network Auto-Regressive (ANNAR) model. Traditional models were tested and compared against the advanced ANNAR model.

Metrics like Root Mean Square Deviation Error, Mean Absolute Error, and Mean Absolute Percentage Error were used to evaluate performance. Surprisingly, the ANNAR model outperformed all others. This finding suggests that more advanced tools can provide better insights for disease prediction. Understanding these trends is crucial for policymakers to allocate resources and Implement effective interventions to combat heart disease in Sindh.

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