Harvard Catalyst Profiles

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Lucy Qing Shen, M.D.

Co-Author

This page shows the publications co-authored by Lucy Shen and Tobias Elze.
Connection Strength

2.830
  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. An Artificial Intelligence Approach to Assess Spatial Patterns of Retinal Nerve Fiber Layer Thickness Maps in Glaucoma. Transl Vis Sci Technol. 2020 08; 9(9):41.
    View in: PubMed
    Score: 0.229
  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. 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
  7. Reply. Ophthalmology. 2018 09; 125(9):e66-e67.
    View in: PubMed
    Score: 0.199
  8. 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
  9. Impact of Natural Blind Spot Location on Perimetry. Sci Rep. 2017 07 21; 7(1):6143.
    View in: PubMed
    Score: 0.185
  10. Relationship Between Central Retinal Vessel Trunk Location and Visual Field Loss in Glaucoma. Am J Ophthalmol. 2017 Apr; 176:53-60.
    View in: PubMed
    Score: 0.178
  11. Clinical Correlates of Computationally Derived Visual Field Defect Archetypes in Patients from a Glaucoma Clinic. Curr Eye Res. 2017 04; 42(4):568-574.
    View in: PubMed
    Score: 0.173
  12. Patterns of functional vision loss in glaucoma determined with archetypal analysis. J R Soc Interface. 2015 Feb 06; 12(103).
    View in: PubMed
    Score: 0.156
  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 Global Test-Retest Variability of Visual Fields in Glaucoma. Ophthalmol Glaucoma. 2021 Jul-Aug; 4(4):390-399.
    View in: PubMed
    Score: 0.058
  15. 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
  16. Monitoring Glaucomatous Functional Loss Using an Artificial Intelligence-Enabled Dashboard. Ophthalmology. 2020 09; 127(9):1170-1178.
    View in: PubMed
    Score: 0.056
  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
  18. Reply. Ophthalmology. 2019 10; 126(10):e78-e79.
    View in: PubMed
    Score: 0.054
  19. Agreement and Predictors of Discordance of 6 Visual Field Progression Algorithms. Ophthalmology. 2019 06; 126(6):822-828.
    View in: PubMed
    Score: 0.051
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.