Schizophrenia is a serious mental disorder with a complex neurobiological background and a well-defined psychopathological picture. Despite many efforts, a definitive disease biomarker has still not been identified. One of the promising candidates fo...
Diabetes Mellitus combined with Mild Cognitive Impairment (DM-MCI) is a high incidence disease among the elderly. Patients with DM-MCI have considerably higher risk of dementia, whose daily self-care and life management (i.e. self-management) have a ...
The advent of smart cities has brought about a paradigm shift in urban management and citizen engagement. By leveraging technological advancements, cities are now able to collect and analyze extensive data to optimize service delivery, allocate resou...
Accurate classification of logos is a challenging task in image recognition due to variations in logo size, orientation, and background complexity. Deep learning models, such as VGG16, have demonstrated promising results in handling such tasks. Howev...
Accurate diagnosis of oral lesions, early indicators of oral cancer, is a complex clinical challenge. Recent advances in deep learning have demonstrated potential in supporting clinical decisions. This paper introduces a deep learning model for class...
Cervical cancer is a deadly disease in women globally. There is a greater chance of getting rid of cervical cancer in case of earliest diagnosis. But for some patients, there is a chance of recurrence. The chances of treating the Recurrence of cervic...
Immune checkpoint inhibitor (ICI) treatment has proven successful for advanced melanoma, but is associated with potentially severe toxicity and high costs. Accurate biomarkers for response are lacking. The present work is the first to investigate the...
With breakthroughs in Natural Language Processing and Artificial Intelligence (AI), the usage of Large Language Models (LLMs) in academic research has increased tremendously. Models such as Generative Pre-trained Transformer (GPT) are used by researc...
Nursing activity recognition has immense importance in the development of smart healthcare management and is an extremely challenging area of research in human activity recognition. The main reasons are an extreme class-imbalance problem and intra-cl...
Novel Human Activity Recognition (HAR) methodologies, which are built upon learning algorithms and employ ubiquitous sensors, have achieved remarkable precision in the identification of sports activities. Such progress benefits all age groups of huma...
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