Integrative multi-stage deep learning framework for ovarian tumor ultrasound classification with explainability and confidence estimation

EfficientOvaNet increases diagnostic accuracy and reduces subjectivity in ultrasound-based ovarian tumor classification. By improving interpretability and credibility, the framework has the potential to support timely intervention and individualized treatment, which may improve survival rates in the management of ovarian cancer.

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Publication Details

Journal
Frontiers in Medicine
Published
2026-02-24
DOI
https://doi.org/10.3389/fmed.2025.1760167
Primary Topic
Ovarian cancer diagnosis and treatment
Type
article
Field-Weighted Citation Impact
0.00

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article

Integrative multi-stage deep learning framework for ovarian tumor ultrasound classification with explainability and confidence estimation

Ahmad Almadhor, Abdullah Al Hejaili, Shtwai Alsubai
Frontiers in Medicine
Ovarian cancer diagnosis and treatment
article

Integrative multi-stage deep learning framework for ovarian tumor ultrasound classification with explainability and confidence estimation

Ahmad Almadhor, Abdullah Al Hejaili, Shtwai Alsubai
article en

Abstract

EfficientOvaNet increases diagnostic accuracy and reduces subjectivity in ultrasound-based ovarian tumor classification. By improving interpretability and credibility, the framework has the potential to support timely intervention and individualized treatment, which may improve survival rates in the management of ovarian cancer.

Frontiers in MedicineVol. 12
Prince Sattam Bin Abdulaziz University (SA), Jouf University (SA), University of Tabuk (SA)
Prince Sattam bin Abdulaziz University
Openalex Percentile: Top 40%
Ovarian cancer diagnosis and treatment
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