Harvard Catalyst Profiles

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Tobias Elze, Ph.D.

Co-Author

This page shows the publications co-authored by Tobias Elze and Michael Boland.
Connection Strength

2.697
  1. The Effect of Ametropia on Glaucomatous Visual Field Loss. J Clin Med. 2021 Jun 25; 10(13).
    View in: PubMed
    Score: 0.243
  2. Development and Comparison of Machine Learning Algorithms to Determine Visual Field Progression. Transl Vis Sci Technol. 2021 06 01; 10(7):27.
    View in: PubMed
    Score: 0.242
  3. Monitoring Glaucomatous Functional Loss Using an Artificial Intelligence-Enabled Dashboard. Ophthalmology. 2020 09; 127(9):1170-1178.
    View in: PubMed
    Score: 0.222
  4. Characterization of Central Visual Field Loss in End-stage Glaucoma by Unsupervised Artificial Intelligence. JAMA Ophthalmol. 2020 02 01; 138(2):190-198.
    View in: PubMed
    Score: 0.220
  5. Artificial Intelligence Classification of Central Visual Field Patterns in Glaucoma. Ophthalmology. 2020 06; 127(6):731-738.
    View in: PubMed
    Score: 0.218
  6. Reply. Ophthalmology. 2019 10; 126(10):e78-e79.
    View in: PubMed
    Score: 0.215
  7. Agreement and Predictors of Discordance of 6 Visual Field Progression Algorithms. Ophthalmology. 2019 06; 126(6):822-828.
    View in: PubMed
    Score: 0.206
  8. An Artificial Intelligence Approach to Detect Visual Field Progression in Glaucoma Based on Spatial Pattern Analysis. Invest Ophthalmol Vis Sci. 2019 01 02; 60(1):365-375.
    View in: PubMed
    Score: 0.205
  9. Reply. Ophthalmology. 2018 09; 125(9):e66-e67.
    View in: PubMed
    Score: 0.199
  10. Reversal of Glaucoma Hemifield Test Results and Visual Field Features in Glaucoma. Ophthalmology. 2018 03; 125(3):352-360.
    View in: PubMed
    Score: 0.189
  11. Impact of Natural Blind Spot Location on Perimetry. Sci Rep. 2017 07 21; 7(1):6143.
    View in: PubMed
    Score: 0.185
  12. Estimating the Severity of Visual Field Damage From Retinal Nerve Fiber Layer Thickness Measurements With Artificial Intelligence. Transl Vis Sci Technol. 2021 08 02; 10(9):16.
    View in: PubMed
    Score: 0.061
  13. Variability and Power to Detect Progression of Different Visual Field Patterns. Ophthalmol Glaucoma. 2021 Apr 20.
    View in: PubMed
    Score: 0.060
  14. Predicting eyes at risk for rapid glaucoma progression based on an initial visual field test using machine learning. PLoS One. 2021; 16(4):e0249856.
    View in: PubMed
    Score: 0.060
  15. Predicting Global Test-Retest Variability of Visual Fields in Glaucoma. Ophthalmol Glaucoma. 2021 Jul-Aug; 4(4):390-399.
    View in: PubMed
    Score: 0.058
  16. Inter-Eye Association of Visual Field Defects in Glaucoma and Its Clinical Utility. Transl Vis Sci Technol. 2020 11; 9(12):22.
    View in: PubMed
    Score: 0.058
  17. Baseline Age and Mean Deviation Affect the Rate of Glaucomatous Vision Loss. J Glaucoma. 2020 01; 29(1):31-38.
    View in: PubMed
    Score: 0.055
Connection Strength
The connection strength for co-authors is the sum of the scores for each of their shared publications.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.