AIMC Topic: B-Lymphocytes

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Identification and Staging of B-Cell Acute Lymphoblastic Leukemia Using Quantitative Phase Imaging and Machine Learning.

ACS sensors
Identification and classification of leukemia cells in a rapid and label-free fashion is clinically challenging and thus presents a prime arena for implementing new diagnostic tools. Quantitative phase imaging, which maps optical path length delays i...

Hematologist-Level Classification of Mature B-Cell Neoplasm Using Deep Learning on Multiparameter Flow Cytometry Data.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
The wealth of information captured by multiparameter flow cytometry (MFC) can be analyzed by recent methods of computer vision when represented as a single image file. We therefore transformed MFC raw data into a multicolor 2D image by a self-organiz...

Discriminant analysis and machine learning approach for evaluating and improving the performance of immunohistochemical algorithms for COO classification of DLBCL.

Journal of translational medicine
BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) is classified into germinal center-like (GCB) and non-germinal center-like (non-GCB) cell-of-origin groups, entities driven by different oncogenic pathways with different clinical outcomes. DLBCL clas...

Large-scale network analysis reveals the sequence space architecture of antibody repertoires.

Nature communications
The architecture of mouse and human antibody repertoires is defined by the sequence similarity networks of the clones that compose them. The major principles that define the architecture of antibody repertoires have remained largely unknown. Here, we...

Staged heterogeneity learning to identify conformational B-cell epitopes from antigen sequences.

BMC genomics
BACKGROUND: The broad heterogeneity of antigen-antibody interactions brings tremendous challenges to the design of a widely applicable learning algorithm to identify conformational B-cell epitopes. Besides the intrinsic heterogeneity introduced by di...

Artificial intelligence-based flow cytometry for the diagnosis of B-cell chronic lymphoproliferative disorders.

Blood advances
Accurate diagnosis of B-cell chronic lymphoproliferative disorders (B-CLPDs) remains challenging due to overlapping phenotypes across subtypes. Machine learning (ML) offers promising tools to improve marker evaluation and refine flow cytometry analys...

Multimarker Assessment of B-Cell and Plasma Cell Subsets and Their Prognostic Role in the Colorectal Cancer Microenvironment.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Although the association between cytotoxic T lymphocytes and favorable prognosis in colorectal cancer is well established, the prognostic significance of B lymphocytes remains more ambiguous. This study aimed to assess the characteristics an...

[CHARACTERIZATION OF THE ADAPTIVE IMMUNE REPERTOIRE USING NEXT GENERATION SEQUENCING: RECENT DISCOVERIES IN THE FIELD OF PRIMARY IMMUNODEFICIENCY, AND THE UPCOMING FUTURE].

Harefuah
A powerful adaptive immune system, which includes cellular (T lymphocytes) and humoral (B lymphocytes) immunity, depends on its ability to recognize and protect against millions of different foreign antigens. It does so through an enormous diverse ar...