Future of Breast Cancer Diagnosis: A Review of DL and ML Applications and Emerging Trends for Multimodal Data

Future of Breast Cancer Diagnosis: A Review of DL and ML Applications and Emerging Trends for Multimodal Data

Breast cancer diagnosis has greatly benefited from the use of deep learning (DL) and machine learning (ML) methods on multimodal data, including mammography, magnetic resonance imaging (MRI), ultrasound, histopathology, genomic data, and clinical reports. Every modality presents its challenges and o...

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Bibliographic Details
Main Authors: Beibit Abdikenov, Tomiris Zhaksylyk, Olzhas Shortanbaiuly, Yerzhan Orazayev, Nursultan Makhanov, Temirlan Karibekov, Victor Suvorov, Aruzhan Imasheva, Kurmash Zhumagozhayev, Aigerim Seitova
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Breast cancer diagnosis
deep learning
genomic data
language models
machine learning
medical imaging
Online Access:https://ieeexplore.ieee.org/document/11062820/
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https://ieeexplore.ieee.org/document/11062820/

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