Insight5 min read
How do you know a health score is right?
Lessons from validating health scores when there is no gold standard
By Ali Eren Karadağ
Turns routine patient data into earlier risk signals and finds overlooked diabetes complications.
Consultation is needed
Hidden risk found
Analysis
Patients reviewed
The Challenge
Critical follow-up tests like HbA1c checks are missed, leaving complication risks undetected.
Nephropathy, retinopathy, and neuropathy develop gradually without visible warning signs.
Risk signals scatter across lab results, referrals, and clinical notes.
Patients needing specialist attention in nephrology or ophthalmology go unidentified.
The Fix
From cohort-level risk discovery to diabetic retinopathy workflow support, AId Core Solutions builds practical decision-support tools for healthcare teams.
AI for Complications of Diabetes
Analyze routine patient data to identify high-risk diabetic patients, care gaps, and follow-up opportunities before they are overlooked.
Built for hospitals, health IT providers, telehealth teams, and preventive health insurers.
4,218
Patients Analyzed
312
High-Risk Identified
1,847
Care Gaps Found
187
Follow-up Opportunities
Decision-support output only. Requires independent clinical review.

AI for Diabetic Retinopathy
Help ophthalmology teams review retinal data, prioritize DR risk, and compare patient history over time.
Blog
Insight5 min read
Lessons from validating health scores when there is no gold standard
By Ali Eren Karadağ
Trusted & Backed
$90K+
Grants, credits & funding
172,000
Patients Trained On
10,000
Real-world patients tested
Invested By
Supported By
















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