Myeloma

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 Autoimmune Haemolytic Anaemia (AIHA) after the last remission.

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 translocation in multiple myeloma (MM). Patients harboring t(11;14) exhibit high response rates to BCL-2 inhibitors, underscoring the importance of rapid detection to guide treatment decisions. While fluorescence in situ hybridization (FISH) remains the gold standard for detecting this abnormality, its...

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 hematologic malignancy that is currently incurable. In...

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...

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) by inhibiting the iron exporter ferroportin in tar...

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 is a clinical need for dose individualization to m...

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 methods for monitoring patients with multiple myelom...

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 screening of βTT to stop spread of the disease. Over...

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 diseases, especially in young children with conditions ...

Investigating CAR-T Treatment Access for Multiple Myeloma Patients Using Real-World Evidence.

OBJECTIVE: Multiple myeloma (MM) is the second most common hematologic malignancy in the U.S., with Black patients being diagnosed at twice the rate o...

A comprehensive case study of deep learning on the detection of alpha thalassemia and beta thalassemia using public and private datasets.

This study explores the performance of deep learning models, specifically Convolutional Neural Networks (CNN) and XGBoost, in predicting alpha and bet...

Machine Learning-Based Prediction of Unplanned Readmission Due to Major Adverse Cardiac Events Among Hospitalized Patients with Blood Cancers.

BackgroundHospitalized patients with blood cancer face an elevated risk for cardiovascular diseases caused by cardiotoxic cancer therapies, which can ...

ShenJiaoLingCao decoction ameliorates cyclophosphamide-induced splenic injury and immunosuppression via the inhibition of MEK/ERK signaling pathway activity and modulation of amino acid metabolism.

ETHNOPHARMACOLOGICAL RELEVANCE: ShenJiaoLingCao Decoction (SJLCD) is derived from the classic Chinese medicine prescription, which consists of ten kin...

MedScale-Former: Self-guided multiscale transformer for medical image segmentation.

Accurate medical image segmentation is crucial for enabling automated clinical decision procedures. However, existing supervised deep learning methods...

Wild horseshoe crab image denoising based on CNN-transformer architecture.

The natural habitats of wild horseshoe crabs (such as beaches, shallow water areas, and intertidal sediments) are complex, posing challenges for image...

Revolutionizing hematological disorder diagnosis: unraveling the role of artificial intelligence.

The integration of artificial intelligence (AI) into medical diagnostics is transforming the landscape of healthcare, particularly in hematology. AI t...

Shengxuebao Mixture improves carboplatin-induced anemia by inhibiting apoptosis and ferroptosis.

ETHNOPHARMACOLOGICAL RELEVANCE: Shengxuebao Mixture (SXB) is a traditional Chinese medicine which has been widely used on treating Chemotherapy-induce...

Individualized dynamic risk assessment and treatment selection for multiple myeloma.

BACKGROUND: Individualized treatment decisions for multiple myeloma (MM) patients require accurate risk stratification that accounts for patient-speci...

Predicting Risk for Patent Ductus Arteriosus in the Neonate: A Machine Learning Analysis.

: Patent ductus arteriosus (PDA) is common in newborns, being associated with high morbidity and mortality. While maternal and neonatal conditions are...

Nutritional predictors of lymphatic filariasis progression: Insights from a machine learning approach.

Lymphatic filariasis (LF) is a mosquito-borne neglected tropical disease that causes disfiguring of the affected extremities, often leading to permane...