AI, Volume 6, Issue 2

Introduction: The Earth’s growing population is increasing resource consumption, heavily pressuring agriculture, which, currently, uses 70% of the world’s freshwater from rivers and lakes, which, themselves, comprise only 1% of the Earth&...

University students often face challenges in managing academic demands and difficulties like time management, task prioritization, and effective study strategies. This scoping review investigates the application of Deep Learning (DL) and Reinforcemen...

Background: Pressure injuries (PIs) are increasing worldwide, and there has been no significant improvement in preventing them. Traditional assessment tools are widely used to identify a patient at risk of developing a PI. This study aims to construc...

Background: Conventional medical image retrieval methods treat images and text as independent embeddings, limiting their ability to fully utilize the complementary information from both modalities. This separation often results in suboptimal retrieva...

Background: Machine learning methods for clinical assistance require a large number of annotations from trained experts to achieve optimal performance. Previous work in natural language processing has shown that it is possible to automatically extrac...

Purpose: The impact of hybrid quantum-classical neural network (NN) architectures with multiple backbones and quantum transformation as a data augmentation (DA) technique on image classification tasks was investigated using the CIFAR-10 and MedMNIST...

Background/Objectives: Artificial intelligence (AI) is transforming higher education (HE), reshaping teaching, learning, and feedback processes. Feedback generated by large language models (LLMs) has shown potential for enhancing student learning out...

The integration of renewable energy sources and electric vehicles has become a focal point for industries and academia due to its profound economic, environmental, and technological implications. These developments require the development of a robust...

Thisstudy introduces a new model for detecting insults in Roman Urdu, filling an important gap in natural language processing (NLP) for low-resource languages. The transliterated nature of Roman Urdu also poses specific challenges from a computationa...

Effectively training deep learning models relies heavily on large datasets, as insufficient instances can hinder model generalization. A simple yet effective way to address this is by applying modern deep learning augmentation methods, as they synthe...