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Abstract The Indian Western Himalayan (IWH) region experiences persistent threats from natural hazards mainly influenced by land use and land cover (LULC) changes resulting from rapid urbanization. The present study aims...

Abstract Preterm birth (PTB) affects an estimated 15 million infants worldwide each year, raising an enormous challenge in the field of maternal-fetal medicine. This work explores machine learning approaches for disting...

Abstract Occupational Health and Safety (OHS), which holds substantial importance due to its profound human implications and far-reaching economic consequences, requires effective management to minimize workplace acciden...

Weaning is a critical stage in swine production, characterized by intestinal alterations that affect piglet health and performance. In this study, machine learning techniques were applied to identify joint patterns betwe...

Abstract Accurate differentiation of pulmonary emphysema from chest X-rays remains challenging due to imbalanced data, image noise, and the limitations of traditional deep networks in managing diagnostic uncertainty. In ...

Abstract Financial institutions continue to face a significant challenge with money laundering and need intelligent, scalable ways to detect illegal financial activity. This paper introduces a machine learning-driven pla...

Abstract In terms of global health, cardiovascular diseases remain an emerging challenge, for which early estimation for timely medical treatment proves crucial. In this paper, an estimate of this challenge has been pres...

Abstract Building energy consumption is dominated by lighting and heating, ventilation, and air conditioning (HVAC) systems, whose operation is often inefficient due to inadequate control strategies and unreliable occupa...

Abstract Feature selection is a critical step in machine learning, as it helps minimize redundant features, thereby enhancing model performance and interpretability. In practice, partially labeled datasets are common. Wh...