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Early Intelligent Diagnosis of Limb Deformity in Children by AI and Clinic Application

The Studies of Early Intelligent Diagnosis of Limb Deformity in Children by AI and Clinic Application

Status
Not yet recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT04527029
Enrollment
9000
Registered
2020-08-26
Start date
2025-03-31
Completion date
2027-12-01
Last updated
2025-02-20

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Limb Deformity

Keywords

Limb deformity; Pediatrics ; Artificial intelligence

Brief summary

The limb deformity in children include congenital limb malformations or acquired from the damage of epiphyseal plate which caused by tumor, inflammation and trauma. Due to the complexity of the disease itself, rapid dynamic development and the characteristics of children's growth and development, the deformities are constantly changing. In addition, the serious lack of clinical diagnosis and treatment resources in the Department of Pediatric Orthopedics has led to the misdiagnosis and improper treatment of children's limb deformities. Thus, its necessary to find an intelligent way to help doctor to early diagnosis of limb deformity and provide a proper treatment in children.

Detailed description

The extraction and application of big data of children's limb deformities, intelligent labeling of image data, precise positioning, and perfecting the anatomical data of children's limb deformities.Improve the positioning accuracy of key points in X-ray images of children's limb deformities by means of step-by-step supervision to improve the accuracy of diagnosis.Realize an intelligent report generation system that combines patient background information, establish an end-to-end auxiliary diagnosis and treatment suggestion demonstration application system; realize a full set of artificial intelligence solutions for children's skeletal deformities, early screening and diagnosis of children, and forming an intelligent referral system of children's limb deformities.

Interventions

OTHERNo interventions

It is an observational study. No interventions.

Sponsors

Children's Hospital of Fudan University
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
No minimum to 18 Years
Healthy volunteers
No

Inclusion criteria

Children with limb deformity

Exclusion criteria

Children without limb deformity

Design outcomes

Primary

MeasureTime frameDescription
Deformity detectionAt enrollmentIt is a binary variable (1/0). The radiographic features of children would be evaluated by artificial Intelligence. If the deformity was detected, variable would be setted into 1.

Contacts

Primary ContactBo Ning, PhD
ningbo@fudan.edu.cn+86 13585700275

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026