Our products enter clinics through journals, not advertising
Every claim on this site is attached to a study someone else reviewed. Four papers are published, four hospitals are running studies, and TÜBİTAK funds the projects that are not products yet.
Publications
Selçuk T., Yılmaz A., et al. Automated assessment of pelvic radiograph appropriateness using deep learning. Acta Orthopaedica et Traumatologica Turcica, 2025.
DOI 10.5152/j.aott.2025.24033
The published basis for the PelSiAn suitability module — symmetry and pelvic tilt assessment on standard AP pelvis films.
Yılmaz A., Selçuk T., et al. Deep-learning measurement of femoroacetabular morphology on standard radiographs. Acta Orthopaedica et Traumatologica Turcica, 2026.
DOI 10.5152/j.aott.2026.25268
Underpins the FAI module: centre-edge, Tönnis and Sharp angles with acetabular coverage.
Selçuk T., et al. Deep-learning classification of dermoscopic lesion imagery. Diagnostics (MDPI), 2024.
DOI 10.3390/diagnostics14182092
The classification work behind NeviTrack's dermoscopy view.
Yılmaz A., et al. Computer-assisted analysis of eye-movement recordings in vestibular assessment. Journal of Clinical Medicine (MDPI), 2024.
DOI 10.3390/jcm13164800
The analysis method vNistagmus builds on for horizontal, vertical and torsional components.
Congresses and exhibitions
Which programme funds what
Where the research runs
Four hospitals, four separate studies, each tied to one product or project.