Bangla news floods the web, and the need for smarter and more efficient classification techniques is greater than ever. Previous studies mostly focused on traditional models, overlooking the potential of hybrid techniques to handle the ever-growing c...
Selecting an effective training signal for machine learning tasks is difficult: expert annotations are expensive, and crowd-sourced annotations may not be reliable. Recent work has demonstrated that learning from a distribution over labels acquired f...
Technical debt prediction (TDP) is crucial for the long-term maintainability of software. In the literature, many machine-learning based TDP models have been proposed; they used TD-related metrics as input features for machine-learning classifiers to...
Experiencing mild symptoms of psychosis, like delusions and hallucinations, occurs sometimes in general, nonclinical populations, often termed psychosis proneness (PP), potentially part of the psychosis continuum. Understanding the neural and environ...
OBJECTIVE: Multi-institutional datasets are widely used for machine learning from clinical data, to increase dataset size and improve generalization. However, deep learning models in particular may learn to recognize the source of a data element, lea...
Reverse vending machines (RVMs) are essential for promoting waste sorting at the source by offering incentives for recycling. However, current RVMs, which primarily rely on expensive sensors such as barcode scanners and computer vision systems, face ...
BioEssays : news and reviews in molecular, cellular and developmental biology
Jun 8, 2025
Organismal evolution is a process of discovering better-fitting phenotypes through trial and error across generations. This iterative process resembles learning processes, an analogy recognized since the 1950s. Recognizing this parallel suggests that...
International journal of medical informatics
Jun 7, 2025
PURPOSE: To summarize and evaluate the methodological quality of primary studies focusing on the use of machine or deep learning- based prediction models for delirium in ICU patients.
International journal of nursing studies
Jun 7, 2025
BACKGROUND: Nursing data can help detect patient deterioration early and predict patient outcomes. Moreover, rapid advancements in machine learning have highlighted the need for clinical prognosis prediction models for intensive care unit patients. A...
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