Myeloma

mRNA vaccines in cancer immunotherapy: current progress and perspectives in solid tumors and hematologic malignancies.

The unprecedented success of mRNA vaccines during the COVID-19 pandemic has accelerated the developm...

Treatment-Specific Prediction Models in Multiple Myeloma: A Critical Review of Current Evidence and Future Directions.

BACKGROUND AND OBJECTIVES: Multiple myeloma (MM) is characterized by substantial clinical heterogene...

FDG-PET Medullary Total Tumor Volume Highlights High-Risk Newly Diagnosed Multiple Myeloma Patients in CASSIOPEIA Trial.

This study aimed to assess the prognostic value of medullary total metabolic tumor volume (mTMTV) de...

FTO-CHRM3 axis regulates multiple myeloma progression: a machine learning-based identification.

BACKGROUND: Fat Mass and Obesity-Associated (FTO) is linked to multiple myeloma (MM) progression, bu...

Integrating machine learning and artificial intelligence in the management of Acinetobacter infections: a narrative review.

Acinetobacter baumannii, particularly in its multidrug-resistant (MDR) and carbapenem-resistant (CRA...

Machine Learning Prediction of Progression to Dialysis in Patients With Polycystic Kidney Disease: Population-Based Retrospective Cohort Study.

BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD), characterized by progressive cyst ...

A complete blood count-based machine learning model for rapid differentiation of aplastic anemia, immune thrombocytopenia, and myelodysplastic syndromes in routine clinical practice.

BACKGROUND: Accurate differentiation of common hematologic disorders remains challenging in routine ...

Dynamic biomarker-based machine learning model predicts short-term treatment response in multiple myeloma.

Toward a cure for multiple myeloma within a decade.

Multiple myeloma (MM), long viewed as incurable, is entering a transformative era marked by deeper r...

Preoperative Risk Score for Mortality Within 3 Years of Elective Aortobifemoral Artery Bypass.

BACKGROUND: The purpose of this study was to create a risk score for mortality within 3 years of ele...

Cross-validation strategies under data dependency: An example with anemia prediction in sheep using ocular conjunctiva images.

Computer vision techniques have been increasingly used in livestock farming for tasks such as animal...

Predictive divergence in machine learning models for clinical mortality risk: A multicohort study of covid-19 patients.

BACKGROUND: Machine learning (ML) algorithms are increasingly used in healthcare to support clinical...

CAR T-cells in hematologic malignancies: Advances, challenges, and future directions.

Chimeric antigen receptor (CAR) T-cell therapy has transformed the management of hematologic maligna...

Comparison of the diagnostic performance of machine learning algorithms for differentiating iron deficiency anemia and thalassemia.

Cutting-Edge Technologies to Decode Tumor Microenvironment in Multiple Myeloma.

Multiple myeloma (MM) is recognized as a malignancy shaped by its complex tumor microenvironment (TM...

A Multi-Omics and machine learning platelet-related prognostic signature in multiple myeloma.

msCNN-PLM-FAD: Enhanced predicting FAD binding sites by using protein language representation combined with multiple separable windows convolutional neural networks.

The FAD binding sites classification problem is crucial because it is directly related to many disea...

A peptide immunomodulator activates MST1 to expand and stabilize murine and human regulatory T cells for immune tolerance.

The expansion and potentiation of regulatory T cells (Treg cells) offer an appealing approach for ac...

Regional brain age is decreased in children with sickle cell anemia.

DeepBrainNet, a machine learning tool, uses magnetic resonance imaging (MRI) to predict an individua...

Regional brain age is decreased in children with sickle cell anemia.

DeepBrainNet, a machine learning tool, uses magnetic resonance imaging (MRI) to predict an individua...

Non-invasive differentiation of light chain amyloidosis and multiple myeloma based on Raman spectroscopy analysis using one-dimensional convolutional neural networks.

Light chain amyloidosis (AL) and multiple myeloma (MM) are interrelated plasma cell disorders charac...