Experience a new standard in ophthalmic-driven insights with the new IDHea® Workplace Screening Dataset—AI-ready, curated, and designed for systemic health breakthroughs.

Built for researchers and innovators across life sciences and healthcare, the Workplace Screening dataset advances longitudinal oculomics research to uncover connections between ophthalmic and systemic health. This resource enables robust biomarker discovery and validation of hidden health signals. Securely integrated within the platform, the dataset accelerates AI model development for predictive and precision medicine, offering unmatched speed, depth, and actionable insights.

Your next big breakthrough starts here.

What makes the Workplace Screening Dataset Powerful for oculomics research?

Here’s what makes the Workplace Screening Dataset stand out:

Oculomics Engine
Instantly link multimodal retinal imaging with 150+ ophthalmic and systemic clinical variables, including blood, urine and biochemical laboratory measurements as well as audiometrics, anthropometrics, metabolics, vitals, medical history and expert, clinical lifestyle recommendations and demographics. Explore connections across multiple health domains, all in one place.

Longitudinal Depth
Track annual health trends and predictive signals six+ years of follow-up data on nearly 17.7K subjects, with ongoing collection. Explore how ophthalmic and systemic health relationships evolve over time.

Data Intelligence Platform
Analyze, iterate, and accelerate insights in a secure, cloud-native environment built for AI-driven research. Access AI-ready data enriched with high quality expert and AI-generated labels - including RETFound - to develop predictive models, validate biomarkers, and explore clinical trial hypotheses, all in a flexible sandbox designed to remove technical barriers and delays.

Relevance for Your Organization

For Academia

Develop and refine AI-driven diagnostic and monitoring tools using multimodal retinal imaging and systemic data.

Drive large-scale, reproducible studies with diverse, longitudinal real-world data for biomarker discovery and epidemiological breakthroughs.

For Pharma

Accelerate biomarker validation for drug development and clinical trials.

Harness labeled AI-ready data to strengthen translational research.

Track disease progression and treatment outcomes with robust, longitudinal follow-up.

For MedTech

Integrate seamlessly into clinical workflows with governed, cloud-based access.

Advance clinical decision-making with real-world, population-scale insights.

Why the Workplace Screening Dataset Sets a New Oculomics Standard

Built for scale, diversity, and depth, this dataset combines multimodal retinal imaging with rich systemic health data, something traditional ophthalmic datasets can’t match.

Our workplace screening datasets deliver comprehensive, research-ready data with robust completeness across clinical categories, ensuring immediate applicability and confident analysis for your research needs.

Table 1: Composition of Data Availability by Clinical Category

Data completeness is 100% across most clinical categories. The few categories below 100% reflect known and expected gaps: Body Composition includes CT‑derived abdominal fat measures collected only for participants with abdominal CT imaging and Vital Signs completeness declined after spirometer measurements were discontinued post‑COVID.

Take a Peek into the Data: Participant Retention & Diagnostic Diversity

Explore the key elements that make this dataset a powerful engine for biomarker discovery, translational research, and precision medicine.

Table 2: Key Dataset Metrics & Descriptions*

Category	Metric Count (N=161)	Description
Metadata — Core dataset descriptors
Demographic	2	Age at first encounter, sex
Image metadata	5	Scan parameters, image quality, device, disc & fovea position
OCT retinal layer analysis	9	Disc (TSNIT and superpixel grids, topography); macula (ETDRS, 6 sector and superpixel grids)
Labels — Categorical assessments
Expert ophthalmic image labels	3	Diabetic retinopathy, arteriosclerotic and hypertensive retinopathy severity
Clinical recommendations	15	Physician recommendations across ocular and systemic domains, metabolic, cardiovascular, renal, and systemic domains
AI-generated labels	10	RETFound features, axial length estimate, glaucoma risk score, AutoMorph segmentations, vascular metrics and retinal pigment score
Clinical data — Clinical measurements and assessments
Audiometry	4	Hearing thresholds at 500, 1000, 2000, and 4000 Hz
Biochemistry	48	Blood and serum biomarkers covering metabolic, lipid, liver, kidney, immune, and infectious markers
Body composition	9	Anthropometrics and body composition indicators
Hematology	15	Blood cell counts, differentials, hemoglobin indices, platelets
Ophthalmology	3	Visual acuity, visual field, optic nerve head assessments
Medical history	12	Self-reported lifestyle and health history, including surgical, family and medication history, and systemic disease treatment status
Urinalysis	19	Urine sample testing and sedimentary analysis, detecting albumin, creatinine, cells, casts, and infection markers
Vital signs	7	Blood pressure, heart rate and spirometric respiratory measures

* See dataset documentation for full definitions and metric/variable lists

Use Cases & Value, Unlocking Research Possibilities

From early detection to predictive modeling, the Workplace Screening Dataset enables applications that drive innovation:

Translational Biomarker Discovery and Validation:
Validate retinal biomarkers for prediction and early intervention using multimodal data and longitudinal follow-up, accelerating the development of clinical tools that integrate visual and systemic signals.

Early Risk Screening:
Detect systemic health risks sooner by analyzing retinal images alongside biochemistry, hematology, and lifestyle data, then track subtle changes over time to support proactive care.

Risk Stratification & Trajectory Modeling:
Model individual risk profiles and health trajectories by combining retinal imaging with systemic biomarkers and lifestyle data, enabling targeted interventions for high-risk groups

These use cases represent just a glimpse of what’s possible, empowering researchers and clinicians to advance early intervention, personalized care, and population health strategies.

Participant Retention & Diagnostic Diversity: Longitudinal Insights

Six years. Nearly 17.7K participants. One dataset built to reveal health trends and power predictive science. Strong participant retention and diagnostic diversity make this dataset a trusted foundation for longitudinal research, enabling studies on disease prevalence, progression, and emerging health trends.

Retention That Builds Confidence
Largest wave of participants joined in Year 1, a typical trend for longitudinal studies. Consistent engagement across subsequent years ensures reliable, real-world data for predictive modeling.

Diagnostic Diversity That Drives Discovery
27 systemic conditions tracked over six years provide unmatched breadth. Annual counts reveal how conditions evolve, delivering a rich, longitudinal view essential for translational research.

distribution-top-5-self-reported-conditions-treatment.png

Accelerate Your Impact in Oculomics Today!

The Workplace Screening Dataset is available now, with the first release including follow-up coverage from 2016 until 2022, giving researchers immediate access to a robust foundation for vision and systemic health research.

Request early access today and unlock a longitudinal dataset that fuses systemic health and ophthalmic imaging data, engineered to accelerate translational research and drive innovation in oculomics.

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Powering Oculomics Research with the IDHea® Workplace Screening Dataset