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IntroductionEarly and accurate diagnosis of skin cancer has a huge impact on the survival rate of patients and deep learning-based CNN and dermatologists' intelligence support can fasten the diagnosis not only within the...

With the consolidation of deep learning in drug discovery, several novel algorithms for learning molecular representations have been proposed. Despite the interest of the community in developing new methods for learning ...

Abstract Understanding human emotions across multiple modalities such as text and images, is increasingly important for applications including content personalization, social media analysis, and Human–Computer Interact...

Purpose – This study critically examines the rapid expansion of artificial intelligence (AI) in digital learning, with a specific focus on how these technologies intersect with metacognitive skills and digital literacy...

Abstract Alzheimer’s disease, a progressive neurodegenerative disorder, presents a growing global health challenge due to its increasing prevalence and lack of accessible early diagnostic methods. Even though it has en...

Computer-aided drug discovery and design involve the use of information technologies to identify and develop, on a rational ground, chemical compounds that align a set of desired physicochemical and biological properties...

Abstract The importance of fear level detection in affective computing using physiological signals has not been extensively explored. Accurately detecting fear responses facilitates real-time emotional monitoring and imp...

ABSTRACT Plant diseases are the cause of heavy losses of crop production and, therefore, a big contributor to food shortages. Identifying these diseases as early as possible is important to limit the negative effects tha...

Abstract Transcriptional regulation, critical for cellular differentiation and adaptation to environmental changes, involves coordinated interactions among DNA sequences, regulatory proteins, and chromatin architecture. ...

Dear Readers,It gives me great pleasure to announce the fourth regular issue of 2026. In this issue, 6 papers by 25 authors from 6 countries - Colombia, Greece, Mexico, Republic of Serbia, South Africa, Türkiye ...

Introduction and aims: Oral and maxillofacial surgery (OMFS) produces complex clinical data, while artificial intelligence (AI) applications in this field remain limited despite great potential. This study aimed to map t...

Blended and flipped classroom pedagogical models are recognised as having the potential to deepen and enrich student learning while also being a more engaging learning experience (Partridge, Ponting, & McCay, 2011). E-le...

"This thesis investigates the application of machine learning methods to the task of deforestation monitoring using time-series satellite data. The objective is to assess how different algorithmic approaches perform in d...