Latest AI and machine learning research in lymphoma for healthcare professionals.
Boolean networks are powerful frameworks for capturing the logic of gene-regulatory circuits, yet ...
Access to safe and clean drinking water remains a critical global challenge, with groundwater as a p...
The TIGPR dataset is a high-quality collection of ground-penetrating radar (GPR) images designed for...
AIM: The aim of this study was to develop a PET-based machine learning model for predicting visceral...
Recently, functional magnetic resonance imaging (fMRI)-based brain networks have been shown to be an...
Glioblastoma (GBM), primary central nervous system lymphoma (PCNSL), and brain metastases (BM) are c...
Non-specific response to treatment (NSRT) is the primary contributor to the failure of randomized cl...
Federated learning (FL) on graph-structured data typically faces non-IID challenges, particularly ...
Accurately localizing the brain regions that triggers seizures and predicting whether a patient wi...
Recent studies have demonstrated that the representations of artificial neural networks (ANNs) can e...
Lung cancer is the leading cause of cancer mortality worldwide, and non-invasive methods for detec...
In online video platforms, accurate watch time prediction has become a fundamental and challenging...
Relapsed or refractory diffuse large B-cell lymphoma (DLBCL) poses significant therapeutic challenge...
We present eACGM, a full-stack AI/ML system monitoring framework based on eBPF. eACGM collects rea...
Purpose: To evaluate the impact of harmonization and multi-region CT image feature integration on ...
Purpose: Magnetic Resonance Imaging (MRI) enables non-invasive assessment of brain abnormalities d...
BACKGROUND: Esophageal cancer is the sixth most common cancer worldwide, with a high mortality rate....
We consider the problem of inferring the conditional independence graph (CIG) of high-dimensional ...
We present a comprehensive analysis of the digest2 parameters for candidates of the Near-Earth Obj...
AI automated segmentations for radiation treatment planning (RTP) can deteriorate when applied in ...
The modernization and globalization of traditional Chinese medicine (TCM) face challenges such as un...