Neoplasms

Urinary Tract, Sexual Organs, and Pregnancy Conditions

All Conditions

Uterine Cervical Neoplasms

Uterine Neoplasms

Genital Neoplasms, Female

Urogenital Neoplasms

Uterine Cervical Diseases

Uterine Diseases

Genital Diseases, Female

Genital Diseases

Urogenital Diseases

Female Urogenital Diseases

Pregnancy Complications

Female Urogenital Diseases and Pregnancy Complications

Using non-image medical data of cervical lesions and clinical pathology results in different medical institutions, machine learning is adopted to establish multiple multi-modal cervical cancer intelligent screening prediction models. This method was used to analyze the prediction performance of the multi-modal cervical cancer intelligent screening prediction and risk triage model, and to evaluate and optimize the self-learning ability of the established multi-modal cervical cancer intelligent screening prediction model.

Artificial intelligence model building

Binhua Dong

Pengming Sun

Fengzhen Zhang

Shaomei Lin

Zheng Zheng

Junbo Hu

By collecting non-image medical data of women undergoing cervical screening in multiple centers in China, including age, HPV infection status, HPV infection type, TCT results, and colposcopy biopsy pathology results, a multi-source heterogeneous cervical lesion collaborative research big data platform was established. Based on artificial intelligence (AI) machine learning, cervical lesion screening features are refined, a multi-modal cervical cancer intelligent screening prediction and risk triage model is constructed, and its clinical application value is preliminarily explored.

By collecting non-image medical data of women undergoing cervical screening in multiple centers in China, including age, HPV infection status, HPV infection type, TCT results, and colposcopy biopsy pathology results, a multi-source heterogeneous cervical lesion collaborative research big data platform was established. Based on artificial intelligence (AI) machine learning, cervical lesion screening features are refined, a multi-modal cervical cancer intelligent screening prediction and risk triage model is constructed, and its clinical application value is preliminarily explored. The effect of clinical application of the model was evaluated by internal data from Fujian Province and external data from several other regions in China.

Model Study on Cervical Cancer Screening Strategies and Risk Prediction

Cervical histopathological diagnosis within 8 weeks

Colposcopists use colposcopic equipment to investigate the occurrence of cervical and vaginal lesions within 8 weeks

Fujian Maternity and Child Health Hospital

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization	Link
Model Study on Cervical Cancer Screening Strategies and Risk Prediction	NCT06204133	Cervical Cancer... Risk Assessment Artificial Inte... Machine Learnin...	Artificial inte...	25 Years - 64 Years	Fujian Maternity and Child Health Hospital
Model Study on Cervical Cancer Screening Strategies and Risk Prediction	NCT06204133	Cervical Cancer... Risk Assessment Artificial Inte... Machine Learnin...	Artificial inte...	25 Years - 64 Years	Fujian Maternity and Child Health Hospital

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