Accurate and timely detection and classification of lung abnormalities are crucial for effective
diagnosis and treatment planning. In recent years, Deep Learning (DL) techniques have …

Recently, there has been a significant advancement in the water quality index (WQI) models
utilizing data-driven approaches, especially those integrating machine learning and artificial …

Diabetes is a chronic disease caused by a persistently high blood sugar level, causing other
chronic diseases, including cardiovascular, kidney, eye, and nerve damage. Prompt …

The research describes an effective deep learning-based, data-centric approach for
diagnosing autism spectrum disorder from facial images. To classify ASD and non-ASD …

Alzheimer's Disease (AD) is a significant cause of dementia worldwide, and its progression
from mild to severe affects an individual's ability to perform daily activities independently …

Atrial Fibrillation (AF) is a common cardiac arrhythmia that can lead to fatal outcomes.
Detecting AF early is crucial for improving patient outcomes and reducing complications …

The Monkeypox outbreak has emerged as a pressing global health challenge, evidenced by
rising cases across nations. Individuals afflicted exhibit diverse dermatological symptoms …

In this study, we propose a novel approach called DCNN-ViT-GRU, which combines deep
Convolutional Neural Networks (CNNs) with Gated Recurrent Units (GRUs) and the Vision …

The traditional complications of diabetes are well known and continue to pose a
considerable burden to millions of people with diabetes mellitus (DM). With the continuous …

Computed tomography (CT) scans play a key role in the diagnosis of stroke, a leading cause
of morbidity and mortality worldwide. However, interpreting these scans is often challenging …