Development of an assessment method for the risk of progression in chronic kidney disease using MRI (magnetic resonance imaging) and artificial intelligence. (a retrospective study)

Construction of an AI assessment system for the risk of CKD progression using renal functional MRI data (a retrospective study) - Construction of an AI assessment system for the risk of CKD progression using renal functional MRI data (a retrospective study)

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000037311

Enrollment

200

Registered

2019-07-15

Start date

2019-07-01

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

Chronic kidney disease

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: A chronic kidney disease patient who underwent MRI at Saitama Medical University for the diagnosis of chronic kidney disease.

Exclusion criteria

Exclusion criteria: After the introduction of renal replacement therapy, children, acute kidney injury, unilateral kidney disease (such as renovascular hypertension), kidney tumors, nephrotic syndrome, cystic disease, and postrenal renal failure

Design outcomes

Primary

Measure	Time frame
Decreases in estimated glomerular filtration rate	—

Countries

Japan

Contacts

Public ContactHirokazu Okada

Saitama Medical University Department of Nephrology

hirookda@saitama-med.ac.jp0492761611

Outcome results