Abstract: System identification is essential for modeling and control of nonlinear dynamic systems. In practice, traditional linear or unidirectional recurrent models often fail to capture the ...
Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...
Early sexual activity, often defined as initiation before 16, is a risky behaviour associated with many negative social and health outcomes. Sexual norms restricting sex till marriage have declined in ...
Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
Aims The obesity paradox has been described in different cardiovascular conditions. Data on the association between obesity and outcomes in patients with Takotsubo syndrome (TTS) are lacking. The aim ...
Information theory and network physiology are rapidly converging fields that offer powerful frameworks for unraveling the complexities of living systems. At ...
This project introduces a diffusion-based framework for symbolic regression, a task traditionally dominated by genetic programming and transformer models. We explore three distinct modeling approaches ...
The final, formatted version of the article will be published soon. Forage legumes play a pivotal role in livestock production, environmental protection, sustainable cropping systems, and various ...
Abstract: Topological indices (TIs) are valuable tools in the study of blood cancer drugs, offering insights into molecular structure and associated properties critical for assessing efficacy and ...
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