Lymphoma

A multi-faceted discovery strategy identifies functional antibodies binding to cysteine-rich domain 1 of hDKK1 for cancer immunotherapy via Wnt non-canonical pathway.

Wnt signaling is important in embryonic development and tumorigenesis. These biological effects can be exerted by the activation of the β-catenin-dependent canonical pathway or the β-catenin-independent non-canonical pathway. DKK1 is a potent inhibitor of Wnt signaling by competing with Wnt binding to LRP5/6 co-receptors. DKK1 is tumorigenic in multiple cancer types and immunosuppressive in NK cel...

Dual-structure community preserving network embedding.

Network embedding, an effective method for learning low-dimensional representations of nodes, plays a crucial role in various network learning scenarios. However, existing network embedding learning methods fail to learn node embeddings from the perspective of the implicit network, leading to embeddings that only incorporate neighborhood details from neighboring nodes across various levels. In thi...

Advancements in Hematologic Malignancy Detection: A Comprehensive Survey of Methodologies and Emerging Trends.

The investigation and diagnosis of hematologic malignancy using blood cell image analysis are major and emerging subjects that lie at the intersection...

Artificial Intelligence Assisted 18F-FDG PET Radiomics in Classifying Histological Subtypes of Lung Cancer: Systematic Review and Meta-analysis.

UNLABELLED: AI-assisted radiomics is an emerging tool for precision oncology, and many studies have recently shown promising results. However, there a...

ProtFun: A Protein Function Prediction Model Using Graph Attention Networks with a Protein Large Language Model.

Understanding protein functions facilitates the identification of the underlying causes of many diseases and guides the research for discovering new t...

2.5D Multi-view Averaging Diffusion Model for 3D Medical Image Translation: Application to Low-count PET Reconstruction with CT-less Attenuation Correction.

Positron Emission Tomography (PET) is an important clinical imaging tool but inevitably introduces radiation exposure to patients and healthcare provi...

Replacing non-biomedical concepts improves embedding of biomedical concepts.

Embeddings are semantically meaningful representations of words in a vector space, commonly used to enhance downstream machine learning applications. ...

Thorax-encompassing multi-modality PET/CT deep learning model for resected lung cancer prognostication: A retrospective, multicenter study.

BACKGROUND: Patients with early-stage non-small cell lung cancer (NSCLC) typically receive surgery as their primary form of treatment. However, studie...

Machine learning approach to single cell transcriptomic analysis of Sjogren's disease reveals altered activation states of B and T lymphocytes.

Sjogren's Disease (SjD) is an autoimmune disorder characterized by salivary and lacrimal gland dysfunction and immune cell infiltration leading to gla...

Forecasting optimal treatments in relapsed/refractory mature T- and NK-cell lymphomas: A global PETAL Consortium study.

There is no standard of care in relapsed/refractory T-cell/natural killer-cell lymphomas. Patients often cycle through cytotoxic chemotherapy (CC), ep...

The Use of Maximum-Intensity Projections and Deep Learning Adds Value to the Fully Automatic Segmentation of Lesions Avid for [F]FDG and [Ga]Ga-PSMA in PET/CT.

This study investigated the added value of using maximum-intensity projection (MIP) images for fully automatic segmentation of lesions using deep lear...

Global burden of non-melanoma skin cancers among older adults: a comprehensive analysis using machine learning approaches.

Non-melanoma skin cancers (NMSCs), including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), have shown significant global increases in ...

B lymphocyte subset-based stratification in primary Sjögren's syndrome: implications for lymphoma risk and personalized treatment.

OBJECTIVE: This study aimed to perform a detailed stratification analysis of B lymphocyte subsets in patients with primary Sjögren's syndrome (pSS) an...

Identification of M2 macrophage-related genes associated with diffuse large B-cell lymphoma via bioinformatics and machine learning approaches.

M2 macrophages play a crucial role in the initiation and progression of various tumors, including diffuse large B-cell lymphoma (DLBCL). However, the ...

Using artificial intelligence-based software for an unbiased discrimination of immune cell subtypes in the fracture hematoma and bone marrow of non-osteoporotic and osteoporotic mice.

It is well established that the early inflammatory response following fracture is essential for initiating subsequent bone regeneration. An imbalance ...

Neural networks for the prediction of bacterial and fungal infections: current evidence and implications.

In the present narrative review, we discuss the use of artificial neural networks (ANNs) for predicting bacterial and fungal infections based on commo...

Ordinal Sleep Depth: A Data-Driven Continuous Measurement of Sleep Depth.

Conventional sleep staging categorises sleep into discrete stages, which may not capture the continuous nature of sleep depth. We aimed to develop a d...

A novel cancer-associated fibroblast-related gene signature for predicting diffuse large B cell lymphoma prognosis using weighted gene co-expression network analysis and machine learning.

ObjectiveOur objective was to investigate a novel cancer-associated fibroblast-related gene signature for predicting clinical outcomes in patients wit...

Clinical performance of a machine learning-based model for detecting lymph node metastasis in papillary thyroid carcinoma: A multicenter study.

Papillary thyroid carcinoma (PTC) is a common endocrine malignancy with a generally favorable prognosis, but lymph node metastasis (LNM) complicates t...

Machine Learning-Enhanced Cerebrospinal Fluid N-Glycome for the Diagnosis and Prognosis of Primary Central Nervous System Lymphoma.

The diagnosis and prognosis of Primary Central Nervous System Lymphoma (PCNSL) present significant challenges. In this study, the potential use of mac...