Mature B-cell neoplasms (MBNs) are clonal proliferative diseases encompassing over 40 subtypes. The WHO classification (morphology, immunology, cytogenetics and molecular biology) provides comprehensive diagnostic understandings. However, MBN subtypi...
The classification of B cell lymphomas-mainly based on light microscopy evaluation by a pathologist-requires many years of training. Since the B cell receptor (BCR) of the lymphoma clonotype and the microenvironmental immune architecture are importan...
To accommodate waning COVID-19 vaccine immunity to emerging SARS-CoV-2 variants, variant-adapted mRNA vaccines have been introduced. Here, we examine serological responses to the BA.1 and BA.4-5 Omicron variant-adapted BNT162b2 COVID-19 vaccines in p...
Engineering immune cells to treat hematological malignancies has been a major focus of research since the first resounding successes of CAR-T-cell therapies in B-ALL. Several diseases can now be treated in highly therapy-refractory or relapsed condit...
Neural networks : the official journal of the International Neural Network Society
Jul 28, 2023
Complementary-label learning (CLL) is widely used in weakly supervised classification, but it faces a significant challenge in real-world datasets when confronted with class-imbalanced training samples. In such scenarios, the number of samples in one...
Cytometry. Part B, Clinical cytometry
Feb 23, 2023
Detection of measurable residual disease (MRD) in chronic lymphocytic leukemia (CLL) is an important prognostic marker. The most common CLL MRD method in current use is multiparameter flow cytometry, but availability is limited by the need for expert...
The use of artificial intelligence methods in the image-based diagnostic assessment of hematological diseases is a growing trend in recent years. In these methods, the selection of quantitative features that describe cytological characteristics plays...
Chronic lymphocytic leukemia (CLL) is the most common blood cancer in adults. The course of CLL and patients' response to treatment are varied. This variability makes it difficult to select the most appropriate treatment regimen and predict the progr...
Artificial intelligence-based tools designed to assist in the diagnosis of lymphoid neoplasms remain limited. The development of such tools can add value as a diagnostic aid in the evaluation of tissue samples involved by lymphoma. A common diagnosti...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.