Natural Language Processing (NLP) has the potential to revolutionise clinical research utilising Electronic Health Records (EHR) through the automated analysis of unstructured free text. Despite this potential, relatively few applications have entere...
BACKGROUND AND OBJECTIVE: The worldwide estimates reveal two-fold increase in incidence of Parkinson's disease (PD) over 25 years. The two-fold increased incidence and lack of proper treatment uplifted a compelling solicitude, nagging towards accurat...
INTRODUCTION: Over one-third of the population in the United States (US) has prediabetes. Unfortunately, underserved population in the United States face a higher burden of prediabetes compared to urban areas, increasing the risk of stroke and heart ...
Alzheimer's disease (AD) is a degenerative neurological condition characterized by a progressive decline in cognitive abilities, resulting in memory impairment and limitations in performing daily tasks. Timely and precise identification of AD holds p...
The variability in image modalities presents significant challenges in medical image classification, as traditional deep learning models often struggle to adapt to different image types, leading to suboptimal performance across diverse datasets. This...
Knee Osteoarthritis (KOA), a leading cause of disability worldwide, is challenging to detect early due to subtle radiographic indicators. Diverse, extensive datasets are needed but are challenging to compile because of privacy, data collection limita...
Sleep apnea, a fatal sleep disorder causing repetitive respiratory cessation, requires immediate intervention due to neuropsychological issues. However, existing approaches such as polysomnography, considered the most reliable and accurate test to de...
Infected region segmentation is crucial for pulmonary infection diagnosis, severity assessment, and monitoring treatment progression. High-performance segmentation methods rely heavily on fully annotated, large-scale training datasets. However, manua...
OBJECTIVES: The current research investigations designates the numerical solutions of the chickenpox disease model by applying a proficient optimization framework based on the artificial neural network. The mathematical form of the chickenpox disease...
The deployment of advanced deep learning models for medical image segmentation is often constrained by the requirement for extensively annotated datasets. Weakly-supervised learning, which allows less precise labels, has become a promising solution t...