Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Attention-based Deep Feature Fusion for Automated Dysarthria Severity Classification: A Speech-based Computational Functional Marker Relevant to Neurovascular and Neurodegenerative Conditions.

Current neurovascular research·2026

Same author

Particle swarm optimization based fusion of ultrasound echographic and elastographic texture features for improved breast cancer detection.

Australasian physical & engineering sciences in medicine·2019

Same journal

Bridging Global Attention and Local Hierarchies: A Robust Hybrid Ensemble Framework With Multi-Perspective Explainability for Automated HER2-IHC Scoring.

Technology in cancer research & treatment·2026

Same journal

Research on Predicting the Efficacy of Immunotherapy for Non-small Cell Lung Cancer Based on CT Radiomics and Peripheral Blood Inflammatory Markers.

Technology in cancer research & treatment·2026

Same journal

Survival Prediction in Patients With Epidermal Growth Factor Receptor-Mutated Non-small Cell Lung Cancer With Bone Metastases Receiving Icotinib Therapy: A Retrospective Observational Study.

Technology in cancer research & treatment·2026

Same journal

Proteomics in Acute Myeloid Leukemia: Current Applications in Precision Medicine and Targeted Immunotherapy.

Technology in cancer research & treatment·2026

Same journal

EML4-ALK in Non-small Cell Lung Cancer: Molecular Mechanisms and Targeted Therapies.

Technology in cancer research & treatment·2026

Same journal

Developing and Validating a Risk Model for Severe Bone Marrow Suppression in Esophageal Cancer Treated with Radiotherapy or Chemoradiotherapy: A Retrospective Cohort Study.

Technology in cancer research & treatment·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jul 27, 2025

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

Review on Deep Learning-Based CAD Systems for Breast Cancer Diagnosis.

S Arun Kumar¹, S Sasikala¹

¹Electronics and Communication Engineering, Kumaraguru College of Technology, Coimbatore, Tamil Nadu, India.

Technology in Cancer Research & Treatment

|June 7, 2023

Summary

This summary is machine-generated.

Deep learning (DL) advances early breast cancer (BC) detection. This review surveys DL and Transfer Learning in computer-aided diagnosis (CAD) for BC, highlighting techniques and performance for improved patient outcomes.

Keywords:

artificial intelligence breast cancer computer-aided diagnosis deep learning detection transfer learning

More Related Videos

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

Integrating Augmented Reality Tools in Breast Cancer Related Lymphedema Prognostication and Diagnosis

Integrating Augmented Reality Tools in Breast Cancer Related Lymphedema Prognostication and Diagnosis

Published on: February 6, 2020

Related Experiment Videos

Last Updated: Jul 27, 2025

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

Integrating Augmented Reality Tools in Breast Cancer Related Lymphedema Prognostication and Diagnosis

Integrating Augmented Reality Tools in Breast Cancer Related Lymphedema Prognostication and Diagnosis

Published on: February 6, 2020

Area of Science:

Medical Imaging and Diagnostics
Artificial Intelligence in Healthcare
Oncology

Background:

Breast Cancer (BC) is a significant health concern for women over 45.
Early BC detection is crucial for reducing mortality rates.
Image-based, non-invasive methods and Computer-Aided Diagnosis (CAD) systems aid radiologists.

Purpose of the Study:

To review recent advancements in Deep Learning (DL) for early breast cancer diagnosis.
To survey various CAD approaches for BC detection and diagnosis.
To provide a detailed overview of DL, Transfer Learning, and DL-based CAD methods.

Main Methods:

Review of state-of-the-art literature on DL and Transfer Learning in BC diagnosis.
Analysis of CAD systems utilizing Machine Learning (ML) and DL.
Comparative study of techniques, datasets, and performance metrics in BC diagnosis literature.

Main Results:

DL approaches offer direct image-based decision-making, unlike feature-driven ML.
The review summarizes current DL techniques enhancing BC diagnosis.
A comparative analysis of existing BC diagnostic methods is presented.

Conclusions:

Deep Learning shows significant promise for improving early breast cancer diagnosis.
DL-based CAD systems are advancing diagnostic accuracy and efficiency.
This review consolidates knowledge on DL applications in breast cancer detection.