MedTrace Logo

Multi-center Application of an AI System for Diagnosis of Cervical Lesions Based on Colposcopy Images

NCT05281939 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 10000

Last updated 2023-11-18

No results posted yet for this study

Summary

The application of artificial intelligence in image recognition of cervical lesions diagnosis has become a research hotspot in recent years. The analysis and interpretation of colposcopy images play an important role in the diagnosis，prevention and treatment of cervical precancerous lesions and cervical cancer. At present, the accuracy of colposcopy detection is still affected by many factors. The research on the diagnosis system of cervical lesions based on multimodal deep learning of colposcopy images is a new and significant research topic. Based on the large database of cervical lesions diagnosis images and non-images, the research group established a multi-source heterogeneous cervical lesion diagnosis big data platform of non-image and image data. Research the lesions segmentation and classification model of colposcopy image based on convolutional neural network, explore the relevant medical data fusion network model that affects the diagnosis of cervical lesions, and realize a multi-modal self-learning artificial intelligence cervical lesion diagnosis system based on colposcopy images. The application efficiency of the artificial intelligence system in the real world was explored through the cohort, and the intelligent teaching model and method of cervical lesion diagnosis were further established based on the above intelligent system.

Conditions

  • Artificial Intelligence
  • Colposcopy
  • Cervical Lesions
  • Image

Interventions

DIAGNOSTIC_TEST

Artificial intelligence diagnosis

Participants were divided into the intervention group and the control group using a random number table. The intervention group participants' cervical colposcopic image data and non-image data as follow：age, the infection of high-risk human papillomavirus (HR-HPV),the type of HR-HPV infection,the duration of HR-HPV infection, cervical cytology (TCT) results, HIV/sexually transmitted infection history, marriage and childbearing history,first sexual life history, sexual partner history, smoking history,oral contraceptives history,the use of immune drug and possible clinical symptoms of cervical lesions such as postcoital bleeding, abnormal vaginal secretions, vaginal bleeding symptoms, etc.

Sponsors & Collaborators

  • Fujian Maternity and Child Health Hospital

    lead OTHER

Principal Investigators

  • Pengming Sun, PhD · Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
TRIPLE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
FEMALE
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2021-08-01
Primary Completion
2024-08-01
Completion
2024-09-01

Countries

  • China

Study Locations

More Related Trials

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 NCT05281939 on ClinicalTrials.gov