Latest AI and machine learning research in lymphoma for healthcare professionals.
Isolated REM sleep behavior disorder (iRBD) is a key prodromal marker of Parkinson's disease (PD), and video-polysomnography (vPSG) remains the diagnostic gold standard. However, manual sleep staging is particularly challenging in neurodegenerative diseases due to EEG abnormalities and fragmented sleep, making PSG assessments a bottleneck for deploying new RBD screening technologies at scale. We a...
Purpose: Large language models (LLMs) are increasingly applied in radiology, but key challenges remain, including data leakage from cloud-based systems, false outputs, and limited reasoning transparency. This study aimed to develop an open-source, offline-deployable retrieval-augmented LLM (RA-LLM) system in which local execution prevents data leakage and retrieval-augmented generation (RAG) impro...
Pregnancy care often involves simultaneous obstetric and other medical conditions, but their co-occurrence patterns are rarely modeled explicitly in a...
Accurate splice site prediction is fundamental to understanding gene expression and its associated disorders. However, most existing models are biased...
Background Stage III colorectal cancer poses a significant threat of metastasis development, as tumour resection and adjuvant chemotherapy do not guar...
High-dimensional neuroimaging data presents challenges for assessing neurodegenerative diseases due to complex non-linear relationships. Variational A...
Background: Delayed or missed diagnosis of congenital heart disease (CHD) contributes to excess pediatric mortality worldwide. Echocardiography (echo)...
Systematic identification of functional non-coding regulatory variants remains a major challenge in human genetics. Conventional approaches such as la...
Graph neural networks (GNNs) have become the standard tool for encoding data and their complex relationships into continuous representations, improvin...
Live cell imaging is uniquely placed to study cell behavior as it preserves spatial context and enables non-destructive observations over time. Integr...
Understanding the role of tertiary lymphoid structures (TLS) is crucial in non-small cell lung cancer (NSCLC), as they are associated with patient pro...
BackgroundPrecision oncology relies heavily on genomic profiling and artificial intelligence to predict therapeutic response in breast cancer. However...
In this paper, we explore several fundamental theoretical issues in cell-based neural architecture search, including whether different architectures i...
Recent advancements in artificial intelligence (AI) and traffic sensing technologies provide significant opportunities for real-time crash risk foreca...
In recent times, graph neural networks (GNNs) have become essential tools in molecular graph learning, due to its ability to model intricate structura...
Primary Central Nervous System Lymphoma (PCNSL) is a rare and aggressive type of hematological malignancy that can pose diagnostic challenges. Early d...
Magnetic resonance imaging (MRI) enables non-invasive, high-resolution analysis of muscle structures. However, automated segmentation remains limite...
Accurate prognosis of non-small cell lung cancer (NSCLC) patients undergoing immunotherapy is essential for personalized treatment planning, enablin...
We consider the problem of learning robust discriminative representations of causally-related latent variables. In addition to observational data, t...
The awareness about moving objects in the surroundings of a self-driving vehicle is essential for safe and reliable autonomous navigation. The inter...