Myeloma

From Laptop to Laboratory: Development and Implementation of a Machine Learning Model for Detecting Iron-Deficiency Anemia.

Multiclass classification of thalassemia types using complete blood count and HPLC data with machine learning.

Mild to severe anemia is caused by thalassemia, a common genetic disorder affecting over 100 countri...

B4GALT3 as a Key Glycosyltransferase Gene in Multiple Myeloma Progression: Insights From Bioinformatics, Machine Learning, and Experimental Validation.

Glycosylation abnormalities are critical in the progression of various cancers. However, their role ...

Predictors of frontline doublet or triplet regimen initiation in transplant-ineligible newly diagnosed multiple myeloma.

AIMS: To identify predictors for initiation of frontline doublet versus triplet therapy for transpla...

A comprehensive targeted panel of 295 genes: Unveiling key disease initiating and transformative biomarkers in multiple myeloma.

BACKGROUND: Multiple myeloma (MM) is a hematological malignancy that progresses from a benign precur...

Comprehensive machine learning analysis of PANoptosis signatures in multiple myeloma identifies prognostic and immunotherapy biomarkers.

PANoptosis is closely associated with tumorigenesis and therapeutic response, yet its role in multip...

Machine Learning for Discriminating Microcytic Hypochromic Anemia Based on Erythrocyte Parameters.

INTRODUCTION: Thalassemia trait (TT) and iron deficiency anemia (IDA) are two common types of microc...

Can we identify individuals at risk to develop multiple myeloma? A machine learning-based predictive model.

Multiple myeloma evolves unnoticed over years, and when diagnosed, organ damage is common. Electroni...

Advanced molecular approaches to thalassemia disorder and the selection of molecular-level diagnostic testing in resource-limited settings.

Beta-thalassemia is a genetic disorder that significantly burdens healthcare systems globally. This ...

Assessing serum thrombopoietin for enhanced diagnosis of ITP, AA, and MDS using machine learning: A retrospective cohort study.

Differentiating between immune thrombocytopenia (ITP), aplastic anemia (AA), and myelodysplastic syn...

Advancing blood cell detection and classification: performance evaluation of modern deep learning models.

The detection and classification of blood cells are important in diagnosing and monitoring a variety...

From Molecular Precision to Clinical Practice: A Comprehensive Review of Bispecific and Trispecific Antibodies in Hematologic Malignancies.

Multispecific antibodies have redefined the immunotherapeutic landscape in hematologic malignancies....

Construction of a predictive model for relapse of primary autoimmune hemolytic anemia: a retrospective cohort study.

OBJECTIVES: To develop a machine learning-based model to predict the relapse risk of Primary Autoimm...

Deep-Learning-Based Prediction of t(11;14) in Multiple Myeloma H&E-Stained Samples.

BACKGROUND: Translocation of chromosomes 11 and 14 [t(11;14)(q13;32)] is the most common primary tra...

Development and validation of a multiple myeloma diagnostic model based on systemic lupus erythematosus-associated genes and identification of specific genes.

BACKGROUND: Monoclonal immunoglobulins are commonly found in multiple myeloma (MM), a prevalent hema...

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 ...

Push Forward Clinical Management of Hematological Toxicity due to Lenalidomide Overexposure: Model-Informed Precision Dosing for Chinese Population With Renal Insufficiency.

Dose-dependent hematological toxicity of lenalidomide has been reported previously, and thus, there ...

Hypoferremic Response to Chronic Inflammation Is Controlled via the Hemojuvelin/Hepcidin/Ferroportin Axis and Does Not Involve Hepcidin-Independent Regulation of Fpn mRNA.

The iron regulatory hormone hepcidin contributes to the pathogenesis of anemia of inflammation (AI) ...

Shortcoming of serum B-cell maturation antigen measurement by enzyme-linked immunosorbent assay in one laboratory's experience: Unsatisfactory assay reproducibility.

INTRODUCTION: Serum protein electrophoresis and serum free light chain (SFLC) assays are standard me...

Detection of β-Thalassemia trait from a heterogeneous population with red cell indices and parameters.

BACKGROUND: India is home to about 42 million people with β-thalassemia trait (βTT) necessitating sc...

Optimizing machine learning models for predicting anemia among under-five children in Ethiopia: insights from Ethiopian demographic and health survey data.

BACKGROUND: Healthcare practitioners require a robust predictive system to accurately diagnose disea...