Myelodysplastic syndrome risk assessment using priority linked correlated feature set using ResNet50-Reference-Cited by-同舟云学术

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Myelodysplastic syndrome risk assessment using priority linked correlated feature set using ResNet50

Published:2024-10 Issue: Volume:96 Page:106597
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Srilakshmi K.^ORCID,Venkata Lakshmi D.

Publisher

Elsevier BV

Reference20 articles.

1. Deep learning application of the discrimination of bone marrow aspiration cells in patients with myelodysplastic syndromes;Lee;Sci. Rep.,2022

2. Personalized Risk Schemes and Machine Learning to Empower Genomic Prognostication Models in Myelodysplastic Syndromes;Awada;Int. J. Mol. Sci.,2022

3. Andrea Acevedo et al., A new convolutional neural network predictive model for the automatic recognition of hypogranulated neutrophils in myelodysplastic syndromes, Comput. Biol. Med. 134 (2021) 104479.

4. Deep learning applications in visual data for benign and malignant hematologic conditions: a systematic review and visual glossary;Srisuwananukorn;Haematologica,2023

5. High-accuracy morphological identification of bone marrow cells using deep learning-based Morphogo system;Lv;Sci. Rep.,2023

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