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Using machine learning techniques to develop risk prediction models for the risk of incident diabetic retinopathy among patients with type 2 diabetes mellitus: a retrospective cohort study

Using machine learning techniques to develop risk prediction models for the risk of incident diabetic retinopathy among patients with type 2 diabetes mellitus: a retrospective cohort study

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2100054246
Enrollment
Unknown
Registered
2021-12-11
Start date
2022-01-01
Completion date
Unknown
Last updated
2022-11-14

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

Conditions

Diabetic retinopathy

Interventions

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risks&#32
of&#32
DR&#32
based&#32
on&#32
machine&#32
learning&#32
(ML)&#32
algorithm.

Sponsors

Dalian Municipal Central Hospital
Lead Sponsor

Eligibility

Sex/Gender
Male
Age
18 Years to 70 Years

Inclusion criteria

Inclusion criteria: 1. Patients in the Department of Endocrinology, Dalian Central Hospital Affiliated to Dalian Medical University from January 2010 to January 2020, hospitalized at least once during the follow-up period; 2. Aged >= 18 years; 3. Diagnosed with type 2 diabetes; 4. Diabetic retinopathy was not diagnosed at the first hospitalization.

Exclusion criteria

Exclusion criteria: Patients with pre-existing eye disease (cataract, glaucoma, or other eye disease).

Design outcomes

Primary

MeasureTime frame
Height;Weight;Age;

Countries

China

Contacts

Public ContactLiu Xuhan

Dalian Central Hospital

xuhanliu281277@163.com+86 13555963206

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026