AIMC Topic: Multiple Myeloma
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Achievability to Extract Specific Date Information for Cancer Research.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Mar 4, 2020
Accurate identification of temporal information such as date is crucial for advancing cancer research which often requires precise date information associated with related cancer events. However, there is a gap for existing natural language processin...
Rapid discrimination of multiple myeloma patients by artificial neural networks coupled with mass spectrometry of peripheral blood plasma.
Scientific reports
May 28, 2019
Multiple myeloma (MM) is a highly heterogeneous disease of malignant plasma cells. Diagnosis and monitoring of MM patients is based on bone marrow biopsies and detection of abnormal immunoglobulin in serum and/or urine. However, biopsies have a singl...
Metabolome
Principal Component Analysis
Metabolic Networks and Pathways
Bone Marrow
Aged, 80 and over
Male
Middle Aged
Case-Control Studies
Immunoglobulins
Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
Multiple Myeloma
Datasets as Topic
Artificial Intelligence
Female
Aged
Humans
Neural Networks, Computer
CGPS: A machine learning-based approach integrating multiple gene set analysis tools for better prioritization of biologically relevant pathways.
Journal of genetics and genomics = Yi chuan xue bao
Sep 13, 2018
Gene set enrichment (GSE) analyses play an important role in the interpretation of large-scale transcriptome datasets. Multiple GSE tools can be integrated into a single method as obtaining optimal results is challenging due to the plethora of GSE to...
Automated Whole-Body Bone Lesion Detection for Multiple Myeloma on Ga-Pentixafor PET/CT Imaging Using Deep Learning Methods.
Contrast media & molecular imaging
Jan 8, 2018
The identification of bone lesions is crucial in the diagnostic assessment of multiple myeloma (MM). Ga-Pentixafor PET/CT can capture the abnormal molecular expression of CXCR-4 in addition to anatomical changes. However, whole-body detection of doze...
Interpretation criteria for FDG PET/CT in multiple myeloma (IMPeTUs): final results. IMPeTUs (Italian myeloma criteria for PET USe).
European journal of nuclear medicine and molecular imaging
Dec 21, 2017
UNLABELLED: ᅟ: FDG PET/CT (F-fluoro-deoxy-glucose positron emission tomography/computed tomography) is a useful tool to image multiple myeloma (MM). However, simple and reproducible reporting criteria are still lacking and there is the need for harmo...
Fully automated classification of bone marrow infiltration in low-dose CT of patients with multiple myeloma based on probabilistic density model and supervised learning.
Computers in biology and medicine
Feb 8, 2016
This paper presents a fully automated method for the identification of bone marrow infiltration in femurs in low-dose CT of patients with multiple myeloma. We automatically find the femurs and the bone marrow within them. In the next step, we create ...
Pharmacokinetics and Safety of Elotuzumab Combined With Lenalidomide and Dexamethasone in Patients With Multiple Myeloma and Various Levels of Renal Impairment: Results of a Phase Ib Study.
Clinical lymphoma, myeloma & leukemia
Dec 21, 2015
INTRODUCTION: The present study evaluated the pharmacokinetics and safety of elotuzumab, a humanized IgG1 monoclonal antibody against signaling lymphocyte activation molecule-F7, combined with lenalidomide and dexamethasone, in patients with multiple...
Middle Aged
Retreatment
Humans
Severity of Illness Index
Neoplasm Staging
Female
Antineoplastic Combined Chemotherapy Protocols
Aged
Kidney Function Tests
Multiple Myeloma
Dexamethasone
Treatment Outcome
Antibodies, Monoclonal, Humanized
Aged, 80 and over
Lenalidomide
Kidney Diseases
Adult
Cytogenetic Analysis
Thalidomide
Male
Comprehensive machine learning analysis of PANoptosis signatures in multiple myeloma identifies prognostic and immunotherapy biomarkers.
Scientific reports
Jul 2, 2025
PANoptosis is closely associated with tumorigenesis and therapeutic response, yet its role in multiple myeloma (MM) remains unclear. This study analyzed bulk transcriptomic and clinical data from the TCGA and GEO databases to identify seven PANoptosi...
Automated vertebrae identification and segmentation with structural uncertainty analysis in longitudinal CT scans of patients with multiple myeloma.
European journal of radiology
Jul 1, 2025
OBJECTIVES: Optimize deep learning-based vertebrae segmentation in longitudinal CT scans of multiple myeloma patients using structural uncertainty analysis.
Evaluating Skellytour for Automated Skeleton Segmentation from Whole-Body CT Images.
Radiology. Artificial intelligence
Mar 1, 2025
Purpose To construct and evaluate the performance of a machine learning model for bone segmentation using whole-body CT images. Materials and Methods In this retrospective study, whole-body CT scans (from June 2010 to January 2018) from 90 patients (...
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