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Using Deep Learning and Radiomics to Diagnose Benign and Malignant Breast Lesions Based on Ultrasound

NCT06069921 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 400

Last updated 2024-06-25

No results posted yet for this study

Summary

This retrospective study aimed to create a prediction model using deep learning and radiomics features extracted from intratumoral and peritumoral regions of breast lesions in ultrasound images, to diagnose benign and malignant breast lesions with BI-RADS 4 classification.

Materials and methods: Patients who visited in The First Affiliated Hospital of Shandong First Medical University ＆ Shandong Provincial Qianfoshan Hospital were collected. Their general clinical features, information on preoperative ultrasound diagnosis, and postoperative pathologic data were reviewed.

Conditions

  • Breast Diseases

Sponsors & Collaborators

  • Ma Zhe

    lead OTHER

Eligibility

Min Age
15 Years
Max Age
80 Years
Sex
FEMALE
Healthy Volunteers
No

Timeline & Regulatory

Start
2015-01-01
Primary Completion
2022-12-30
Completion
2022-12-30

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06069921 on ClinicalTrials.gov