PURPOSE: Intestinal obstruction surgery is a high-risk procedure associated with postoperative sepsis. In this multicenter retrospective study, we aimed to employ machine-learning methods to predict sepsis after intestinal obstruction surgery and vis...
Dynamic Bayesian Networks (DBNs) are probabilistic models with a directional structure employed to model temporal processes. Three approaches to DBN structure learning are constraint-based, score-based, and hybrid. The score criterion determined in t...
Mental health disorders affect over 15% of the global working-age population, contributing to an annual economic loss of approximately USD 1 trillion due to diminished productivity and increased healthcare expenditures. In India, the post-pandemic su...
Integrating machine learning (ML) into nanotechnology represents a promising strategy for rational design and accelerated development of drug delivery systems. However, studies in this field are scarce and face methodological and interpretative probl...
The financial sector has experienced swift growth over recent years, leading to the escalating prominence of credit risk among publicly traded companies. Consequently, forecasting credit risk for these firms has emerged as a critical task for banks, ...
Species Distribution Models (SDMs) are widely used in ecology to analyze historical and future patterns of marine species distributions. Given the growing impact of climate change, predicting potential shifts in species ranges has become a key challe...
Mental health is a crucial aspect of overall well-being, yet it is often overlooked due to stigma and limited accessibility to care. This study investigates the ability of artificial intelligence (AI) to predict common psychological conditions, depre...
Sparse numerical datasets are dominant in fields such as applied mathematics, astronomy, finance, and healthcare, presenting challenges due to their high dimensionality and sparse distribution. The predominance of zero values complicates optimal feat...
Educational data mining has become an effective tool for exploring the hidden relationships in educational data and predicting students' academic performance. Educational evaluation is an important part of the teaching process, and the traditional ev...
BACKGROUND: Machine learning (ML) has shown great potential in recognizing complex disease patterns and supporting clinical decision-making. Diabetic foot ulcers (DFUs) represent a significant multifactorial medical problem with high incidence and se...
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