Hybrid time series and machine learning models for forecasting cardiovascular mortality in India: an age specific analysis
Abstract Cardiovascular disease (CVD) is a primary cause of death in India, accounting for a significant portion of the global CVD burden. This study looks at statistics on heart disease mortality from the Institute for Health Metrics and Evaluation (IHME) from 1990 to 2021, divided into five age gr...
Saved in:
| Main Authors: | M Darshan Teja, G Mokesh Rayalu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-06-01
|
| Series: | BMC Public Health |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12889-025-23318-7 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A hybrid approach to time series forecasting: Integrating ARIMA and prophet for improved accuracy
by: Sherly A, et al.
Published: (2025-09-01) -
Time series modelling and forecasting of mpox incidence and mortality in Nigeria
by: Emmanuel Afolabi Bakare, et al.
Published: (2025-06-01) -
Modeling and forecasting of egg production in india using time series models
by: Abdullah Mohammad Ghazi Al Khatib, et al.
Published: (2021-12-01) -
Time series forecasting of infant mortality rate in India using Bayesian ARIMA models
by: Anuj Singh, et al.
Published: (2025-08-01) -
Quantitative and intelligent methods for economic forecasts (birth rate time series (Ntl))
by: Katerina ZELA
Published: (2024-04-01)