ArticleFrontiers in medicine2024
Ultrasound radiomics-based artificial intelligence model to assist in the differential diagnosis of ovarian endometrioma and ovarian dermoid cyst.
Article in Frontiers in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 4 of them syntheses that pooled it.
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Who cites it
11 citing papers in PubMed, 4 syntheses or guidelines pooled it, 14 citations in OpenAlex.
- Artificial intelligence in ovarian pathophysiology and management: a systematic review and meta-analysis.Journal of ovarian research · 2026Pooled it
- Application of artificial intelligence to ultrasound imaging for benign gynecological disorders: systematic review.Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology · 2025Pooled it
- Artificial intelligence for ovarian cancer diagnosis via ultrasound: a systematic review and quantitative assessment of model performance.Frontiers in artificial intelligence · 2025Pooled it
- Diagnostic accuracy of machine learning for endometriosis: a systematic review and meta-analysis.Frontiers in endocrinology · 2025Pooled it
- MRI-based radiomics analysis and machine learning in the differentiation of endometriomas from hemorrhagic ovarian cysts.European journal of radiology open · 2026Article
- Radiomics and Artificial Intelligence in Ovarian Endometriosis Imaging: A Systematic Review and Critical Appraisal of Emerging Evidence.Bioengineering (Basel, Switzerland) · 2026Review
- Artificial intelligence potential in ovarian endometriosis imaging: a comparative meta-analysis of transvaginal ultrasound-based AI models and human readers.Abdominal radiology (New York) · 2026Review
- Multitask deep learning models for ultrasound image analysis: identification of high-grade serous ovarian cancer and segmentation of tumor regions and intratumoral solid components.Journal of ovarian research · 2026Article
- Pediatric nasal dermoid sinus cysts: advances in pathogenesis, management strategies, and translational research-a multidisciplinary management perspective.Frontiers in pediatrics · 2025Review
- Segmentation of ovarian cyst in ultrasound images using AdaResU-net with optimization algorithm and deep learning model.Scientific reports · 2024Article
- Enhancing Ovarian Tumor Diagnosis: Performance of Convolutional Neural Networks in Classifying Ovarian Masses Using Ultrasound Images.Journal of clinical medicine · 2024Article
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Accurately differentiating between ovarian endometrioma and ovarian dermoid cyst is of clinical significance. However, the ultrasound appearance of these two diseases is variable, occasionally causing confusion and overlap with each other. This study aimed to develop a diagnostic classification model based on ultrasound radiomics to intelligently distinguish and diagnose the two diseases. Methods: We collected ovarian ultrasound images from participants diagnosed as patients with ovarian endometrioma or ovarian dermoid cyst. Feature extraction and selection were performed using the Mann-Whitney Results: A total of 407 participants with 407 lesions were included and categorized into the ovarian endometriomas group ( Conclusion: This ultrasound radiomics-based model demonstrated superior diagnostic performance compared to those of junior radiologists and comparable diagnostic performance to those of senior radiologists, and it has the potential to enhance the diagnostic performance of junior radiologists.
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