Andrew D. Graham

1.1k total citations
52 papers, 858 citations indexed

About

Andrew D. Graham is a scholar working on Public Health, Environmental and Occupational Health, Ophthalmology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Andrew D. Graham has authored 52 papers receiving a total of 858 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Public Health, Environmental and Occupational Health, 25 papers in Ophthalmology and 23 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Andrew D. Graham's work include Ocular Surface and Contact Lens (35 papers), Glaucoma and retinal disorders (23 papers) and Corneal surgery and disorders (21 papers). Andrew D. Graham is often cited by papers focused on Ocular Surface and Contact Lens (35 papers), Glaucoma and retinal disorders (23 papers) and Corneal surgery and disorders (21 papers). Andrew D. Graham collaborates with scholars based in United States, Brazil and United Kingdom. Andrew D. Graham's co-authors include Meng C. Lin, Kenneth A. Polse, Thao N. Yeh, Richard Brand, Nancy McNamara, Robert E. Fusaro, Ming‐Chih Lin, Steve Selvin, Lori A. Lott and Clifton M. Schor and has published in prestigious journals such as PLoS ONE, Journal of Fluid Mechanics and Scientific Reports.

In The Last Decade

Andrew D. Graham

48 papers receiving 826 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Andrew D. Graham United States 17 659 439 387 127 90 52 858
Nancy Keir Canada 15 676 1.0× 408 0.9× 335 0.9× 118 0.9× 70 0.8× 38 779
Adrian S. Bruce Australia 17 899 1.4× 604 1.4× 487 1.3× 125 1.0× 61 0.7× 49 1.0k
Kathryn Dumbleton Canada 16 748 1.1× 495 1.1× 342 0.9× 184 1.4× 56 0.6× 26 919
Cristina M. Schnider United States 14 671 1.0× 423 1.0× 359 0.9× 135 1.1× 39 0.4× 38 870
Ping Situ Canada 17 1.0k 1.6× 489 1.1× 478 1.2× 167 1.3× 96 1.1× 48 1.2k
María J. Giráldez Spain 17 443 0.7× 388 0.9× 388 1.0× 136 1.1× 57 0.6× 78 793
Cécile Maïssa United Kingdom 18 1.2k 1.9× 628 1.4× 572 1.5× 126 1.0× 164 1.8× 55 1.4k
Leo G. Carney Australia 20 695 1.1× 690 1.6× 581 1.5× 380 3.0× 54 0.6× 107 1.2k
Doris Richter Canada 10 598 0.9× 366 0.8× 310 0.8× 133 1.0× 34 0.4× 21 709
Carlos García‐Resúa Spain 16 398 0.6× 350 0.8× 396 1.0× 101 0.8× 49 0.5× 60 644

Countries citing papers authored by Andrew D. Graham

Since Specialization
Citations

This map shows the geographic impact of Andrew D. Graham's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Andrew D. Graham with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew D. Graham more than expected).

Fields of papers citing papers by Andrew D. Graham

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew D. Graham. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Andrew D. Graham. The network helps show where Andrew D. Graham may publish in the future.

Co-authorship network of co-authors of Andrew D. Graham

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew D. Graham. A scholar is included among the top collaborators of Andrew D. Graham based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Andrew D. Graham. Andrew D. Graham is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Graham, Andrew D., et al.. (2025). Artificial intelligence models utilize lifestyle factors to predict dry eye related outcomes. Scientific Reports. 15(1). 13378–13378. 1 indexed citations
2.
3.
Graham, Andrew D., et al.. (2024). A machine learning approach to predicting dry eye-related signs, symptoms and diagnoses from meibography images. Heliyon. 10(17). e36021–e36021. 3 indexed citations
4.
Graham, Andrew D. & Meng C. Lin. (2021). The relationship of pre-corneal to pre-contact lens non-invasive tear breakup time. PLoS ONE. 16(6). e0247877–e0247877. 5 indexed citations
5.
Graham, Andrew D., et al.. (2019). Not All Dry Eye in Contact Lens Wear Is Contact Lens–Induced. Eye & Contact Lens Science & Clinical Practice. 46(4). 214–222. 12 indexed citations
6.
Tan, Bo, Andrew D. Graham, Gavriil Tsechpenakis, & Meng C. Lin. (2014). A Novel Analytical Method Using OCT to Describe the Corneoscleral Junction. Optometry and Vision Science. 91(6). 650–657. 27 indexed citations
7.
Graham, Andrew D., et al.. (2013). Factors in Contact Lens Symptoms. Optometry and Vision Science. 91(2). 133–141. 45 indexed citations
8.
Yeh, Thao N., et al.. (2013). Relationships among Tear Film Stability, Tear Osmolarity, Corneal Staining History, and Dryness Symptoms. Investigative Ophthalmology & Visual Science. 54(15). 4332–4332. 2 indexed citations
9.
Vedamurthy, Indu, Meng C. Lin, Jianliang Tong, et al.. (2012). Does Ethnicity Influence the Short-Term Adaptation to First Reading Correction?. Optometry and Vision Science. 89(4). 435–445. 1 indexed citations
10.
Graham, Andrew D., et al.. (2011). Effects of Eye Rubbing and Breath Holding on Corneal Biomechanical Properties and Intraocular Pressure. Cornea. 30(8). 855–860. 34 indexed citations
11.
Graham, Andrew D., et al.. (2008). Clinical Assessment vs. Subjective Experience of Dry Eye in Soft Contact Lens Wearers. Investigative Ophthalmology & Visual Science. 49(13). 4831–4831. 4 indexed citations
12.
Graham, Andrew D., et al.. (2008). Subjective Ratings of Comfort and Dryness vs. Clinical Evaluation of Lens Performance and Ocular Response to Silicone Hydrogel Lenses: Evidence From a Multi-Study Database. Investigative Ophthalmology & Visual Science. 49(13). 4833–4833. 1 indexed citations
13.
Giasson, Claude, et al.. (2005). Morphometry of Cells and Guttae in Subjects With Normal or Guttate Endothelium With a Contour Detection Algorithm. Eye & Contact Lens Science & Clinical Practice. 31(4). 158–165. 11 indexed citations
14.
Fusaro, Robert E., et al.. (2001). The Berkeley Contact Lens Extended Wear Study: part I. Ophthalmology. 108(8). 1381–1388. 5 indexed citations
15.
Lanzl, Ines, et al.. (2000). Does Head Positioning Influence Anterior Chamber Depth in Pseudoexfoliation Syndrome?. Journal of Glaucoma. 9(3). 214–218. 20 indexed citations
16.
Schor, Clifton M., et al.. (1999). Saccades reduce latency and increase velocity of ocular accommodation. Vision Research. 39(22). 3769–3795. 33 indexed citations
17.
Graham, Andrew D., Robert E. Fusaro, & Kenneth A. Polse. (1998). Automating Data Entry and Validation in Clinical Research. American Journal of Obstetrics and Gynecology. 202(6). 594.e1–4. 2 indexed citations
18.
Adams, Craig W., et al.. (1996). Acceptance of auto-refractor and clinician prescriptions: A randomized clinical trial. Investigative Ophthalmology & Visual Science. 37(3). 8 indexed citations
19.
Bullimore, Mark A., et al.. (1995). PATIENT ACCEPTANCE OF AUTO-REFRACTOR AND OPTOMETRIST PRESCRIPTIONS: A RANDOMIZED CLINICAL TRIAL. Optometry and Vision Science. 72(SUPPLEMENT). 97–97. 1 indexed citations
20.
Adams, Craig W., et al.. (1994). RELIABILITY OF THE HOYA AR570 AUTOREFRACTOR. Optometry and Vision Science. 71(Supplement). 82–82.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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