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Multiple Myeloma

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Prediction of Bone Marrow Biopsy Results From MRI in Multiple Myeloma Patients Using Deep Learning and Radiomics.

Investigative radiology
OBJECTIVES: In multiple myeloma and its precursor stages, plasma cell infiltration (PCI) and cytogenetic aberrations are important for staging, risk stratification, and response assessment. However, invasive bone marrow (BM) biopsies cannot be perfor...

Dose reduction and toxicity of lenalidomide-dexamethasone in multiple myeloma: A machine-learning prediction model.

Journal of oncology pharmacy practice : official publication of the International Society of Oncology Pharmacy Practitioners
PURPOSE: Lenalidomide remains an effective drug for multiple myeloma, but it is often associated with adverse events and requires dose adjustments. The objective of this study was to propose a model for predicting whether a patient would require dose...

Detection of circulating plasma cells in peripheral blood using deep learning-based morphological analysis.

Cancer
BACKGROUND: The presence of circulating plasma cells (CPCs) is an important laboratory indicator for the diagnosis, staging, risk stratification, and progression monitoring of multiple myeloma (MM). Early detection of CPCs in the peripheral blood (PB...

Deep Learning Enables Spatial Mapping of the Mosaic Microenvironment of Myeloma Bone Marrow Trephine Biopsies.

Cancer research
UNLABELLED: Bone marrow trephine biopsy is crucial for the diagnosis of multiple myeloma. However, the complexity of bone marrow cellular, morphologic, and spatial architecture preserved in trephine samples hinders comprehensive evaluation. To dissec...

Artificial intelligence-based, volumetric assessment of the bone marrow metabolic activity in [F]FDG PET/CT predicts survival in multiple myeloma.

European journal of nuclear medicine and molecular imaging
PURPOSE: Multiple myeloma (MM) is a highly heterogeneous disease with wide variations in patient outcome. [F]FDG PET/CT can provide prognostic information in MM, but it is hampered by issues regarding standardization of scan interpretation. Our group...

3D CNN-based Deep Learning Model-based Explanatory Prognostication in Patients  with Multiple Myeloma using Whole-body MRI.

Journal of medical systems
Although magnetic resonance imaging (MRI) data of patients with multiple myeloma (MM) are used to predict prognosis, few reports have applied artificial intelligence (AI) techniques for this purpose. We aimed to analyze whole-body diffusion-weighted ...

Artificial Intelligence Individualized Risk Classifier in Multiple Myeloma.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology

Construction of the prediction model for multiple myeloma based on machine learning.

International journal of laboratory hematology
INTRODUCTION: The global burden of multiple myeloma (MM) is increasing every year. Here, we have developed machine learning models to provide a reference for the early detection of MM.