Latest AI and machine learning research in lymphoma for healthcare professionals.
This study aimed to develop a deep-learning (DL) based method for three-dimensional (3D) segmentatio...
INTRODUCTION: Artificial intelligence image recognition has applications in clinical practice. The p...
Dedicated brain imaging for cancer patients is seldom recommended in the absence of symptoms. There ...
BACKGROUND: Hypodontia is the most prevalent dental anomaly in humans, and is primarily attributed t...
Sarcopenia is a comprehensive degenerative disease with the progressive loss of skeletal muscle mass...
IMPORTANCE: Convolutional neural networks (CNN) have shown performance equal to trained dermatologis...
OBJECTIVE: Clinical visual intraoperative electrocorticography (ioECoG) reading intends to localize ...
SIGNIFICANCE: Accurate cell segmentation and classification in three-dimensional (3D) images are vit...
Graph Contrastive Learning (GCL) generates graph-level embeddings by maximizing Mutual Information b...
BACKGROUND: Accurately assessing 5-year recurrence rates is crucial for managing non-muscle-invasive...
Artificial intelligence and Internet of Things are playing an increasingly important role in monitor...
INTRODUCTION: We propose a novel approach for the non-invasive quantification of dynamic PET imaging...
BACKGROUND: Non-Alcoholic Steatohepatitis (NASH) is a crucial stage in the progression of Non-Alcoho...
Anemia is a significant global health issue, affecting over a billion people worldwide, according to...
PURPOSE: Intraoperative hypotension is associated with adverse outcomes. Predicting and proactively ...
Sign language is undoubtedly a common way of communication among deaf and non-verbal people. But it ...
Dynamic 2-[18F] fluoro-2-deoxy-D-glucose positron emission tomography (dFDG-PET) for human brain ima...
Lupus nephritis (LN) is a challenging condition with limited diagnostic and treatment options. In th...
Primary diffuse central nervous system large B-cell lymphoma (CNS-pDLBCL) and high-grade glioma (HGG...
We aimed to build a deep learning-based pathomics model to predict the early recurrence of non-muscl...
Radiomics, analysing quantitative features from medical imaging, has rapidly become an emerging fiel...