The development of digital learning environments has generated rich educational data capable of supporting early prediction of student outcomes. In this study, seven diverse datasets, spanning demographics, parental education, assessment history, and... read more
Journal of imaging informatics in medicine
Apr 28, 2026
Age and gender estimation are crucial in forensic odontology for identification and legal purposes. Conventional methods utilizing manual interpretation like Demirjian's and Gustafson's techniques are labor-intensive and prone to observer bias. Deep ... read more
Journal of imaging informatics in medicine
Apr 28, 2026
Artificial intelligence-based computer-aided diagnosis (CADx) systems have seen growing adoption in mammography, yet the limited interpretability of their decision-making processes remains a barrier to clinical trust. The present study aimed to inves... read more
Artificial intelligence (AI) is gaining importance in the field of cardiology. By analyzing complex multimodal data AI can support the diagnostic processes, risk stratification and making decisions. In cardiac imaging AI-based procedures improve the ... read more
Understanding our world which is open and diverse requires foundation models that generalize well while trustworthy. Adversarial training has been considered to be one of the most effective strategies to achieve robust learning systems, yet adversari... read more
Single-molecule tracking in living cells measures protein diffusivity but requires sparse imaging, limiting high-density mapping. Here we introduce single-molecule localization and diffusivity microscopy (SMLDM), a deep learning-based approach that a... read more
Inflammation research : official journal of the European Histamine Research Society ... [et al.]
Apr 28, 2026
BACKGROUND: Severe asthma is characterized by persistent airway inflammation and epithelial injury. Pyroptosis, a Caspase-1-dependent inflammatory cell death pathway, has been implicated in airway inflammation. FBXW7, an E3 ubiquitin ligase involved ... read more
No machine learning (ML) models for predicting delivery mode after labor induction (IOL) have been externally validated. We aimed to develop and validate one using medical records. Portuguese tertiary center data (nā=ā2434) were used for development ... read more
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