Exploration of the Application of Multimodal Feature Analysis Based on Random Forest Algorithm Combining Ultrasound Elastography and Contrast-Enhanced Ultrasound in the Diagnosis of Ovarian Tumors

Q: How does OCRA curate its research paper database?

OCRA indexes peer-reviewed papers from PubMed and CrossRef, enriched with MeSH terms, author profiles, and citation metrics. Papers are categorized by cancer type, research method, and clinical relevance.

Q: Can I search papers by MeSH term or author?

Yes. Use the search bar to filter papers by MeSH term, author name, journal, keyword, or cancer type. Each paper includes linked MeSH terms and author profiles for further exploration.

Q: How current is the paper database?

The database is updated regularly through automated ingestion from PubMed and CrossRef. Most papers appear within days of their PubMed indexing date.

doi:10.1016/j.ultrasmedbio.2025.12.013

Exploration of the Application of Multimodal Feature Analysis Based on Random Forest Algorithm Combining Ultrasound Elastography and Contrast-Enhanced Ultrasound in the Diagnosis of Ovarian Tumors

Qi Li & Xinxian Gu et al. · 2026-02-02

Links

DOI PubMed

Journal

Ultrasound in Medicine & Biology

TL;DR

The multimodal ultrasound-RF model constructed in this study exhibits excellent diagnostic performance and quantifies the contribution of key features, providing a reliable imaging tool for the early and precise diagnosis of ovarian malignancies.

AI-generated by Semantic Scholar

Authors

Qi Li, Peijin Zhang, Tao Jiang, Yonghong Luo, Xinxian Gu

Funding

Wuhu Municipal Science and Technology Bureau Funding Anhui Science and Technology Department Funding