Workplace Screening

Last updated March 2026
Last updated March 2026

Tags:REAL-WORLD DATAScreeningOculomicsSystemicMaestroColor Fundus PhotographyOptical Coherence TomographyVisual FieldDiabetic RetinopathyHypertensive RetinopathyArteriosclerotic ChangesMedical HistoryAudiometryHematologyBiochemistryUrinalysisMetabolicVitals

This ongoing longitudinal oculomics dataset tracks the overall health and wellbeing from over 17,000 individuals undergoing annual workplace screening by a corporate healthcare screening provider in Japan, at present over a 6-year period.

The dataset comprises extensive systemic electronic medical records including self-reported medical history, vital signs, biochemical, hematological, audiometric, and urinary measurements, with paired optical coherence tomography (OCT) and color fundus photography (CFP).

1

Location

17.7K

Subjects

32K

Eyes

93K

Images

REQUEST DATASETS

Data overview

Dataset attributesDetails
Publishing frequency

New major versions of the dataset will be released periodically with additional data collected from the existing site.

Follow-up coverage

1 year – 6 years

Years collected

2016 - 2022

Version

Version 1 (February 2026)

Geographic coverage

Japan

Locations

1

Devices

Maestro (Topcon Corp., Tokyo, Japan)

Imaging modalities

Optical coherence tomography, color fundus photography

Image formats

DICOM

Details

Age, sex

Scan size, scan resolution, fixation, TopQ image quality, OCT focus mode, model name, fovea position, disc center position

Disc: TSNIT circle (4 sector, 12 sector, 36 sector), disc topography (e.g. disc / cup / rim area and volume, CD ratio, disc diameter)  Macula: Superpixel, 6 sector, and ETDRS grid retinal layer thicknesses

LabelsDetails
Model-generated data

AutoMorph¹ segmentations, image quality predictions, vascular metrics

Axial length estimate²

Multi-factorial OCT score³

RETFound⁴ extracted features (academic and non-commercial research use only)

Retinal pigment score⁵

Expert image labels

Severity of diabetic retinopathy was graded according to the diabetic retinopathy Fukuda classification⁶ and mapped to the international classification for diabetic retinopathy (ICDR) using the Diabetic Retinopathy Clinical Practice Guideline from the Japanese Society of Ophthalmic Diabetology⁷.

Grading for arteriosclerotic changes in the retina from color fundus photographs based on the Scheie classification⁸, a clinical grading scale describing vascular narrowing and arteriovenous crossing changes.

Grading for hypertensive retinopathy changes in the retina from color fundus photographs grading based on the Scheie classification⁸, a clinical grading scale describing hemorrhages and other hypertensive signs.

Clinical recommendations

Clinical recommendations provided by a medical professional after annual exam. Individual recommendations provided after evaluating results from a subject’s fundus image, visual field, visual acuity, hematology, blood pressure, lipids, glucose metabolism, immunity, liver function, lung function, uric acid, urinalysis, body mass index and hearing.

Recommendations are classified into seven categories. No abnormal findings were observed; Minor findings were noted, but they are not of concern; Subject must pay attention to lifestyle habits and monitor any changes in symptoms; Subject should receive regular health guidance from an occupational physician or public health nurse; A detailed examination at a medical institution is necessary for the findings indicated; Subject should follow their primary doctor’s instructions and continue treatment; A re-examination is needed for the findings indicated.

Clinical dataDetails
Audiometry

Hearing test results at four different frequencies: 500Hz, 1000Hz, 2000Hz, and 4000Hz.

Biochemistry

Laboratory test results from blood or serum samples spanning biochemical, metabolic, immunological, and serological markers used to assess overall health, including lipid, metabolic, infectious disease, enzyme, kidney, and liver function.

Hematology

Laboratory measurements assessing blood cell counts and morphology, including red and white blood cell parameters, differential leukocyte counts, hemoglobin indices, hematocrit, and platelet levels.

Body composition

Measurements and indicators capturing body composition and anthropometrics, including weight, fat distribution and height-based metrics.

Ophthalmology

Ophthalmic assessments, including visual acuity, visual field and optic nerve head status.

Medical history

Self-reported survey responses on marital status, average sleep, smoking status, alcohol consumption, medical history, surgical history, family history and medication status.

Urinalysis

Urinalysis measurements evaluating kidney function, hydration status, and urinary abnormalities, including urine chemistry values, albumin, creatinine, and tests for the presence of blood, glucose, ketones, cells, casts, bacteria, and other indicators of urinary tract or metabolic conditions.

Vital signs

Physiological measurements of respiratory function and cardiovascular status, including spirometric measures of lung capacity and airflow, as well as pulse rate, and systolic and diastolic blood pressure readings.

References

  1. Zhou Y, Wagner SK, Chia MA, Zhao A, Woodward-Court P, Xu M, et al. AutoMorph: Automated retinal vascular morphology quantification via a deep learning pipeline. Transl Vis Sci Technol. 2022 Jul 8;11(7):12.
  2. Ko TH, Hsiao YS, Kubota A, Akiba M, Hou H, Durbin M. Axial length estimation using automated OCT scans. Invest Ophthalmol Vis Sci. 2024 July 16;65(9):PB00106–PB00106.
  3. Fukai K, Terauchi R, Noro T, Ogawa S, Watanabe T, Nakagawa T, et al. Real-time risk score for glaucoma mass screening by spectral domain optical coherence tomography: Development and validation. Transl Vis Sci Technol. 2022 Aug 1;11(8):8. 
  4. Zhou Y, Chia MA, Wagner SK, Ayhan MS, Williamson DJ, Struyven RR, et al. A foundation model for generalizable disease detection from retinal images. Nature. 2023 Oct;622(7981):156–63.
  5. Rajesh AE, Olvera-Barrios A, Warwick AN, Wu Y, Stuart KV, Biradar MI, et al. Machine learning derived retinal pigment score from ophthalmic imaging shows ethnicity is not biology. Nat Commun. 2025 Jan 2;16(1):1–14.
  6. Fukuda, Masatoshi. "Classification and treatment of diabetic retinopathy." Diabetes research and clinical practice 24 (1994): S171-S176.
  7. Japanese Society of Ophthalmic Diabetology. Diabetic Retinopathy Clinical Practice Guideline. 1st ed. Available from: https://www.nichigan.or.jp/Portals/0/resources/member/guideline/diabetic_retinopathy.pdf. Accessed 2026 Jan 21.
  8. Lang GK. Ophthalmology: A Pocket Textbook Atlas. Stuttgart: Thieme; 2007.

Data overview

Dataset attributes

Publishing frequency

New major versions of the dataset will be released periodically with additional data collected from the existing site.

Follow-up coverage

1 year – 6 years

Years collected

2016 - 2022

Version

Version 1 (February 2026)

Geographic coverage

Japan

Locations

1

Devices

Maestro (Topcon Corp., Tokyo, Japan)

Imaging modalities

Optical coherence tomography, color fundus photography

Image formats

DICOM

Metadata

Demographic

Age, sex

Image metadata

Scan size, scan resolution, fixation, TopQ image quality, OCT focus mode, model name, fovea position, disc center position

OCT Analysis

Disc: TSNIT circle (4 sector, 12 sector, 36 sector), disc topography (e.g. disc / cup / rim area and volume, CD ratio, disc diameter)  Macula: Superpixel, 6 sector, and ETDRS grid retinal layer thicknesses

Labels

Model-generated data

AutoMorph¹ segmentations, image quality predictions, vascular metrics

Axial length estimate²

Multi-factorial OCT score³

RETFound⁴ extracted features (academic and non-commercial research use only)

Retinal pigment score⁵

Expert image labels

Severity of diabetic retinopathy was graded according to the diabetic retinopathy Fukuda classification⁶ and mapped to the international classification for diabetic retinopathy (ICDR) using the Diabetic Retinopathy Clinical Practice Guideline from the Japanese Society of Ophthalmic Diabetology⁷.

Grading for arteriosclerotic changes in the retina from color fundus photographs based on the Scheie classification⁸, a clinical grading scale describing vascular narrowing and arteriovenous crossing changes.

Grading for hypertensive retinopathy changes in the retina from color fundus photographs grading based on the Scheie classification⁸, a clinical grading scale describing hemorrhages and other hypertensive signs.

Clinical recommendations

Clinical recommendations provided by a medical professional after annual exam. Individual recommendations provided after evaluating results from a subject’s fundus image, visual field, visual acuity, hematology, blood pressure, lipids, glucose metabolism, immunity, liver function, lung function, uric acid, urinalysis, body mass index and hearing.

Recommendations are classified into seven categories. No abnormal findings were observed; Minor findings were noted, but they are not of concern; Subject must pay attention to lifestyle habits and monitor any changes in symptoms; Subject should receive regular health guidance from an occupational physician or public health nurse; A detailed examination at a medical institution is necessary for the findings indicated; Subject should follow their primary doctor’s instructions and continue treatment; A re-examination is needed for the findings indicated.

Clinical data

Audiometry

Hearing test results at four different frequencies: 500Hz, 1000Hz, 2000Hz, and 4000Hz.

Biochemistry

Laboratory test results from blood or serum samples spanning biochemical, metabolic, immunological, and serological markers used to assess overall health, including lipid, metabolic, infectious disease, enzyme, kidney, and liver function.

Hematology

Laboratory measurements assessing blood cell counts and morphology, including red and white blood cell parameters, differential leukocyte counts, hemoglobin indices, hematocrit, and platelet levels.

Body composition

Measurements and indicators capturing body composition and anthropometrics, including weight, fat distribution and height-based metrics.

Ophthalmology

Ophthalmic assessments, including visual acuity, visual field and optic nerve head status.

Medical history

Self-reported survey responses on marital status, average sleep, smoking status, alcohol consumption, medical history, surgical history, family history and medication status.

Urinalysis

Urinalysis measurements evaluating kidney function, hydration status, and urinary abnormalities, including urine chemistry values, albumin, creatinine, and tests for the presence of blood, glucose, ketones, cells, casts, bacteria, and other indicators of urinary tract or metabolic conditions.

Vital signs

Physiological measurements of respiratory function and cardiovascular status, including spirometric measures of lung capacity and airflow, as well as pulse rate, and systolic and diastolic blood pressure readings.

References

  1. Zhou Y, Wagner SK, Chia MA, Zhao A, Woodward-Court P, Xu M, et al. AutoMorph: Automated retinal vascular morphology quantification via a deep learning pipeline. Transl Vis Sci Technol. 2022 Jul 8;11(7):12.
  2. Ko TH, Hsiao YS, Kubota A, Akiba M, Hou H, Durbin M. Axial length estimation using automated OCT scans. Invest Ophthalmol Vis Sci. 2024 July 16;65(9):PB00106–PB00106.
  3. Fukai K, Terauchi R, Noro T, Ogawa S, Watanabe T, Nakagawa T, et al. Real-time risk score for glaucoma mass screening by spectral domain optical coherence tomography: Development and validation. Transl Vis Sci Technol. 2022 Aug 1;11(8):8. 
  4. Zhou Y, Chia MA, Wagner SK, Ayhan MS, Williamson DJ, Struyven RR, et al. A foundation model for generalizable disease detection from retinal images. Nature. 2023 Oct;622(7981):156–63.
  5. Rajesh AE, Olvera-Barrios A, Warwick AN, Wu Y, Stuart KV, Biradar MI, et al. Machine learning derived retinal pigment score from ophthalmic imaging shows ethnicity is not biology. Nat Commun. 2025 Jan 2;16(1):1–14.
  6. Fukuda, Masatoshi. "Classification and treatment of diabetic retinopathy." Diabetes research and clinical practice 24 (1994): S171-S176.
  7. Japanese Society of Ophthalmic Diabetology. Diabetic Retinopathy Clinical Practice Guideline. 1st ed. Available from: https://www.nichigan.or.jp/Portals/0/resources/member/guideline/diabetic_retinopathy.pdf. Accessed 2026 Jan 21.
  8. Lang GK. Ophthalmology: A Pocket Textbook Atlas. Stuttgart: Thieme; 2007.