Brain tumors pose a severe health risk, often leading to fatal outcomes if not detected early. While most studies focus on improving classification accuracy, this research emphasizes prediction certainty, quantified through loss values. Traditional m...
INTRODUCTION: Emotion recognition systems have traditionally relied on basic visual elicitation. Virtual reality (VR) offers an immersive alternative that better resembles real-world emotional experiences.
Parkinson's disease (PD) is a neurodegenerative disorder that occurs as a result of a decrease in the chemical called dopamine in the brain. There is no definitive treatment for PD, but some medications used to control symptoms in the early stages ha...
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by a progressive cognitive decline, necessitating early diagnosis for effective treatment. This study presents the Relational Bi-level Aggregation Graph Convolutional Network with...
BACKGROUND: Assessing the extent of inflammation in peritubular capillaries (PTCs) is important for diagnosing antibody-mediated rejection in kidney transplant biopsies. However, this assessment is time-consuming and suffers from interobserver variab...
This review paper comprehensively examines recent advancements in machine learning (ML) applications within biofluid mechanics, with a targeted focus on enabling clinically actionable diagnostics and simulations. It demonstrates how ML, and in partic...
This paper presents a novel method for weakly-supervised semantic segmentation (WSSS) of histology images, where only global image-level labels are employed. We leverage an existing weakly-supervised object localization (WSOL) method to generate clas...
Considering the high incidence of osteoarthritis (OA), especially of the knee and hip, this study explores the possible genetic associations between OA and cancer types, including cancers of the bladder, kidney, breast, and prostate. The objective of...
Medical image super-resolution (SR) is a classic regression task in low-level vision. Limited by hardware limitations, acquisition time, low radiation dose, and other factors, the spatial resolution of some medical images is not sufficient. To addres...
RATIONALE AND OBJECTIVES: Deep learning (DL)-based methods show promise in detecting pulmonary embolism (PE) on CT pulmonary angiography (CTPA), potentially improving diagnostic accuracy and workflow efficiency. This meta-analysis aimed to (1) determ...