Machine Learning–Based Prediction of Long-Term Intraocular Pressure Fluctuations in Open-Angle Glaucoma
Colya N Englisch, André M Trouvain, Philip Wakili, Moritz J Wolf, H Burkhard Dick, Kaweh Mansouri, Esther M Hoffmann, Marc J Mackert, Achim Langenbucher, Jan Alexandersson, Karl T Boden, Peter Szurman · 2026
Read Machine Learning–Based Prediction of Long-Term Intraocular Pressure Fluctuations in Open-Angle Glaucoma by Colya N Englisch, André M Trouvain, Philip Wakili, Moritz J Wolf, H Burkhard Dick, Kaweh Mansouri, Esther M Hoffmann, Marc J Mackert, Achim Langenbucher, Jan Alexandersson, Karl T Boden, Peter Szurman (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13284456.txt.
Description
Colya Englisch and co-authors, in a 2026 study, test whether machine learning can foresee long term swings in eye pressure for people with open angle glaucoma. High and shifting pressure inside the eye drives this disease, which slowly harms sight. A sensor placed in the eye can send pressure readings from daily life, far beyond clinic visits.
Twenty four patients joined the study, most with the common primary form of the disease. Their sensor data was averaged over day and night cycles, with the first 90 days after surgery left out. The team paired each day with a later day at fixed gaps, and asked how well short spans of one to four weeks foretold swings about nine months to a year ahead. Standard correlation tools weighed those links, as a base for learned prediction.
Catalog record
| CREATOR | Colya N Englisch, André M Trouvain, Philip Wakili, Moritz J Wolf, H Burkhard Dick, Kaweh Mansouri, Esther M Hoffmann, Marc J Mackert, Achim Langenbucher, Jan Alexandersson, Karl T Boden, Peter Szurman |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 35 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |