A decades-long study of nearly 200,000 adults challenges the low-carb versus low-fat debate. Both eating patterns were tied to lower heart disease risk when they emphasized whole grains, plant-based ...
Abstract: Heart disease remains the leading cause of mortality worldwide, highlighting the need for accurate and interpretable risk prediction models. This study proposes Hybrid Tabular Network with ...
A decision tree regression system incorporates a set of if-then rules to predict a single numeric value. Decision tree regression is rarely used by itself because it overfits the training data, and so ...
Hybrid Quantum-Classical Algorithm for an Integrated Feature Selection and Logistic Regression Model
Abstract: Feature selection is a pivotal step in machine learning, aimed at reducing feature dimensionality and improving model performance. Conventional feature selection methods, typically framed as ...
Cardiovascular and metabolic health are influenced by the circadian system, which regulates 24-hour rhythms across numerous physiologic processes. Disruptions to circadian rhythmicity can adversely ...
Background Early identification of patients at risk of heart failure (HF) provides opportunities for preventative management. Though models have been developed to predict HF incidence, their ...
The Rally Point is a regular column where the inimitable Sin Vega delves deep into strategy gaming. Centuries ago, before 2022, before the Good Darkness of 2020, before the Before Times of 2015, the ...
Dubious data sets are being used to train artificial-intelligence models that are designed to predict people’s risk of stroke and diabetes, researchers report in a preprint 1 on medRxiv. Some of the ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results