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A Deep Learning Algorithm Platform to Predict Autism Diagnosis and Subtypes

NCT04873674 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 420

Last updated 2023-10-17

No results posted yet for this study

Summary

This is the first human study on ASD microbiome with robust methodologies: prospective and sibling designs, metagenomics profiles, establishing an ASD multi-dimensional databank (clinic, behavior, neurocognition, brain imaging, metabolomics, and microbiome) collected using the same methodology and genetic biology simultaneously, and developing a deep learning platform for ASD diagnosis and prevention. With the accomplishment of this project, we anticipate establishing a web application for clinical and academic use. Our findings will further advance the knowledge in the pathogenetic mechanisms of ASD to enhance early detection, diagnosis, and treatment, subsequently contributing to precision medicine.

Conditions

Interventions

OTHER

ASD diagnosis

Autism Diagnostic Interview-revised (ADI-R) and Autism Diagnostic Observation Scale (ADOS)

OTHER

Psychiatric diagnosis

Kiddie Schedule for Affective Disorders \& Schizophrenia (K-SADS) for DSM-5

Sponsors & Collaborators

  • National Taiwan University Hospital

    lead OTHER

Eligibility

Min Age
4 Years
Max Age
25 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-05-01
Primary Completion
2024-04-30
Completion
2024-04-30

Countries

  • Taiwan

Study Locations

More Related Trials

Entities

Diseases

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 NCT04873674 on ClinicalTrials.gov