Evaluation of precision diagnosis using artificial intelligence (AI) diagnostic software for chest X-ray: For practical use in medical and health care for lung cancer treatment

Evaluation of precision diagnosis using artificial intelligence (AI) diagnostic software for chest X-ray: For practical use in medical and health care for lung cancer treatment - Evaluation of precision diagnosis using artificial intelligence (AI) diagnostic software for chest X-ray: For practical use in medical and health care for lung cancer treatment

Status

Recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000049204

Enrollment

31000

Registered

2022-11-01

Start date

2021-11-01

Completion date

Unknown

Last updated

2026-06-29

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

Conditions

Respiratory disease

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: The case that a normal X-rays diagnosis can enforce The image that 1750x1750 pixel is more than it in resolution of the X-rays image which I used for shooting

Exclusion criteria

Exclusion criteria: The image that image quality and a shooting condition have a problem It is the image with the defect in DICOM information The image which a manager for study studied it and judged to be inappropriate

Design outcomes

Primary

Measure	Time frame
Regarding to Ministry of Health, Labour and Welfare recommending "the process index in the lung cancer examination", we aim recall rate 3% or less, lung cancer discovery rate 0.03% or more, and Positive Predictive Value 1.3% or more	—

Countries

Japan

Contacts

Public ContactHisashi Saji

St. Marianna University School of Medicine Chest Surgery

saji-q@ya2.so-net.ne.jp044-977-8111

Outcome results