Hematology

Myeloma

Latest AI and machine learning research in myeloma for healthcare professionals.

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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 ...

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 Netwo...

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 ...

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

Accurate medical image segmentation is crucial for enabling automated clinical decision procedures. ...

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 s...

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

The integration of artificial intelligence (AI) into medical diagnostics is transforming the landsca...

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

ETHNOPHARMACOLOGICAL RELEVANCE: Shengxuebao Mixture (SXB) is a traditional Chinese medicine which ha...

Individualized dynamic risk assessment and treatment selection for multiple myeloma.

BACKGROUND: Individualized treatment decisions for multiple myeloma (MM) patients require accurate r...

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 mor...

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 ...

Metabolomics and machine learning approaches for diagnostic biomarkers screening in systemic light chain amyloidosis.

Delayed diagnosis of systemic light chain (AL) amyloidosis is common and associated with worse survi...

Bone-wise rigid registration of femur, tibia, and fibula for the tracking of temporal changes.

BACKGROUND: Multiple myeloma (MM) induces temporal alterations in bone structure, such as osteolytic...

Inhibition of CDC27 O-GlcNAcylation coordinates the antitumor efficacy in multiple myeloma through the autophagy-lysosome pathway.

Multiple myeloma (MM) is a prevalent hematologic malignancy characterized by abnormal proliferation ...

Assessment of anemia recovery using peripheral blood smears by deep semi-supervised learning.

Monitoring anemia recovery is crucial for clinical intervention. Morphological assessment of red blo...

Preoperative anemia is an unsuspecting driver of machine learning prediction of adverse outcomes after lumbar spinal fusion.

BACKGROUND CONTEXT: Preoperative risk assessment remains a challenge in spinal fusion operations. Pr...

Ultrasensitive Detection of Circulating Plasma Cells Using Surface-Enhanced Raman Spectroscopy and Machine Learning for Multiple Myeloma Monitoring.

Multiple myeloma is a hematologic malignancy characterized by the proliferation of abnormal plasma c...

Optimizing papermaking wastewater treatment by predicting effluent quality with node-level capsule graph neural networks.

Papermaking wastewater consists of a sizable amount of industrial wastewater; hence, real-time acces...

Genomic determinants of biological age estimated by deep learning applied to retinal images.

With the development of deep learning (DL) techniques, there has been a successful application of th...

A machine learning tool for early identification of celiac disease autoimmunity.

Identifying which patients should undergo serologic screening for celiac disease (CD) may help diagn...

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