Predictive modeling of biomedical temporal data in healthcare applications: review and future directions
Predictive modeling of clinical time series data is challenging due to various factors. One
such difficulty is the existence of missing values, which leads to irregular data. Another …
such difficulty is the existence of missing values, which leads to irregular data. Another …
[HTML][HTML] Optimization of multidimensional feature engineering and data partitioning strategies in heart disease prediction models
S Wang, L Zhang, X Liu, J Sun - Alexandria Engineering Journal, 2024 - Elsevier
The relentless rise in heart disease incidence, a leading global cause of death, presents a
significant public health challenge. Precise prediction of heart disease risk and early …
significant public health challenge. Precise prediction of heart disease risk and early …
VAR Model with Sparse Group LASSO for Multi-population Mortality Forecasting
TJ Boonen, Y Chen - Available at SSRN 4955315, 2024 - papers.ssrn.com
We introduce a spatial-temporally weighted vector autoregressive (SWVAR) model for
modeling and forecasting mortality rates across multiple populations. First, we stack the …
modeling and forecasting mortality rates across multiple populations. First, we stack the …
[PDF][PDF] The short-term association between environmental variables and mortality: evidence from Europe
Using fine-grained, publicly available data, this paper studies the short-term association
between environmental factors, ie, weather and air pollution characteristics, and weekly …
between environmental factors, ie, weather and air pollution characteristics, and weekly …