Artificial Intelligence Clinical Trial
Official title:
Multi-center Application of an Artificial Intelligence System for Automatic Real-time Diagnosis of Cervical Lesions Based on Colposcopy Images
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.
Status | Recruiting |
Enrollment | 10000 |
Est. completion date | September 1, 2024 |
Est. primary completion date | August 1, 2024 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | Female |
Age group | 18 Years and older |
Eligibility | Inclusion Criteria: - Married woman - Woman aged 18 and over - Woman with an intact cervix - Patients with abnormal results in cervical cancer screening - Be able to understand this study and have signed a written informed consent Exclusion Criteria: - Woman with acute reproductive tract inflammation - History of pelvic radiotherapy surgery - Woman with mental disorder - Patients with history of other malignant tumors - Refuse to participate in this study |
Country | Name | City | State |
---|---|---|---|
China | Fujian Maternity and Child Health Hospital | Fuzhou | Fujian |
China | Jianou Maternal and child Health Care Hospital | Nanping | |
China | Mindong Hospital of Ningde City | Ningde | Fujian |
China | Ningde Hospital affiliated to Ningde Normal University | Ningde | |
China | Quanzhou First Hospital | Quanzhou |
Lead Sponsor | Collaborator |
---|---|
Fujian Maternity and Child Health Hospital |
China,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | HPV testing | Cervical exfoliated cells were collected for HPV testing | o month | |
Primary | Cervical cytology testing | Cervical exfoliated cells were collected for cytological and pathological examination. | 0 month | |
Primary | Cervical histopathological examination | Cervical tissue was collected for histopathological examination | 0 month | |
Primary | Accuracy of CIN2+ diagnosis | Accuracy in the diagnosis of cervical intraepithelial neoplasia grade 2 or worse. | 0 month | |
Primary | Accuracy of CIN3+ diagnosis | Accuracy in the diagnosis of cervical intraepithelial neoplasia grade 3 or worse. | 0 month |
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