Latest AI and machine learning research in lymphoma for healthcare professionals.
Deep learning-based automated segmentation of vascular structures in preoperative CT angiography (CT...
UNLABELLED: Study aims and objectives. This study aims to evaluate the accuracy of medical knowledge...
BACKGROUND: A high portal pressure gradient (PPG) is associated with an increased risk of failure to...
OBJECTIVE: To investigate how different combinations of T1-weighted (T1w), T2-weighted (T2w), and di...
BACKGROUND: Non-small cell lung cancer (NSCLC) is one of the leading causes of cancer mortality worl...
BACKGROUND: The clinical care process for people with prediabetes starts with lifestyle intervention...
The SINFONIA project's main objective is to develop novel methodologies and tools that will provide ...
The contamination of mycotoxins is a serious problem around the world. It has detrimental effects on...
HLA-DRB1*04:01 is associated with numerous diseases, including sclerosis, arthritis, diabetes, and C...
BACKGROUND: This study aimed to develop a machine learning classifier for predicting intraoperative ...
Geobacillus thermoglucosidasius NCIMB 11955 possesses advantages, such as high-temperature tolerance...
The color of skin lesions is a crucial diagnostic feature for identifying malignant melanoma and oth...
Motor brain-machine interfaces (BMIs) decode neural signals to help people with paralysis move and c...
Identifying interactions between long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) provides a ne...
Cervical cancer can be detected at an early stage through the changes occurring in biochemical and m...
INTRODUCTION: Non-alcoholic fatty liver disease (NAFLD) represents a major global health challenge, ...
Regulatory non-coding RNAs (ncRNAs) are increasingly recognized as integral to the control of biolog...
PURPOSE: In the current clinical diagnostic process, the gold standard for lymph node metastasis (LN...
Over 50 million people globally suffer from Alzheimer's disease (AD), emphasizing the need for effic...
Graph Neural Networks (GNNs) play a key role in efficiently learning node representations of graph-s...
BACKGROUND: Non-communicable diseases (NCDs) are a major public health challenge globally, including...