Clinical trial NCT04527029: Early Intelligent Diagnosis of Limb Deformity in Children by AI and Clinic Application
Official title: The Studies of Early Intelligent Diagnosis of Limb Deformity in Children by AI and Clinic Application
Study type: OBSERVATIONAL
Overall status: NOT_YET_RECRUITING
Conditions: Limb Deformity
Keywords: Limb deformity; Pediatrics ; Artificial intelligence
Lead sponsor: Children's Hospital of Fudan University
Sponsor class: OTHER
First posted: 2020-08-26
Enrollment: 9000
Sex: ALL
Maximum age (years): 18
Standard ages: CHILD
ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Children with limb deformity

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.

Eligibility criteria: Inclusion Criteria:

Children with limb deformity

Exclusion Criteria:

Children without limb deformity

Primary outcomes:
measure: Deformity detection
timeFrame: At enrollment
Secondary outcomes:
Other outcomes:
Locations:
Study officials:
affiliation: Children's Hospital of Fudan University
name: Bo Ning, PhD
role: PRINCIPAL_INVESTIGATOR
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