Daniel M. Gore

876 total citations
18 papers, 592 citations indexed

About

Daniel M. Gore is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Daniel M. Gore has authored 18 papers receiving a total of 592 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Radiology, Nuclear Medicine and Imaging, 9 papers in Ophthalmology and 7 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Daniel M. Gore's work include Corneal surgery and disorders (18 papers), Corneal Surgery and Treatments (16 papers) and Glaucoma and retinal disorders (9 papers). Daniel M. Gore is often cited by papers focused on Corneal surgery and disorders (18 papers), Corneal Surgery and Treatments (16 papers) and Glaucoma and retinal disorders (9 papers). Daniel M. Gore collaborates with scholars based in United Kingdom, Mexico and Czechia. Daniel M. Gore's co-authors include Bruce Allan, Stephanie L. Watson, J. Rozema, Alex Ferdi, Vuong Nguyen, Alex J. Shortt, Chris Dunsby, P. M. W. French, David O’Brart and Stephen J. Tuft and has published in prestigious journals such as Ophthalmology, American Journal of Ophthalmology and Investigative Ophthalmology & Visual Science.

In The Last Decade

Daniel M. Gore

16 papers receiving 571 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel M. Gore United Kingdom 12 567 307 254 123 12 18 592
Hala El Rami Lebanon 11 392 0.7× 303 1.0× 153 0.6× 80 0.7× 12 1.0× 20 468
Miguel Romero-Jiménez Portugal 7 625 1.1× 265 0.9× 402 1.6× 156 1.3× 12 1.0× 8 652
Woong-Joo Whang South Korea 10 255 0.4× 240 0.8× 98 0.4× 165 1.3× 13 1.1× 42 336
Sashia Bak‐Nielsen Denmark 9 512 0.9× 302 1.0× 235 0.9× 118 1.0× 11 0.9× 11 546
L. Trinh France 11 354 0.6× 313 1.0× 224 0.9× 122 1.0× 11 0.9× 28 467
M.Á. Del Buey Spain 10 241 0.4× 229 0.7× 113 0.4× 75 0.6× 28 2.3× 21 342
Daniël A. Godefrooij Netherlands 15 1.1k 1.9× 569 1.9× 516 2.0× 176 1.4× 11 0.9× 22 1.1k
Gianni Petrocelli Italy 14 526 0.9× 354 1.2× 169 0.7× 93 0.8× 7 0.6× 23 553
Preeji S. Mandathara India 12 292 0.5× 132 0.4× 279 1.1× 78 0.6× 7 0.6× 16 342
Damian Lake United Kingdom 13 288 0.5× 267 0.9× 104 0.4× 62 0.5× 7 0.6× 29 362

Countries citing papers authored by Daniel M. Gore

Since Specialization
Citations

This map shows the geographic impact of Daniel M. Gore'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 Daniel M. Gore with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel M. Gore more than expected).

Fields of papers citing papers by Daniel M. Gore

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel M. Gore. 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 Daniel M. Gore. The network helps show where Daniel M. Gore may publish in the future.

Co-authorship network of co-authors of Daniel M. Gore

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel M. Gore. A scholar is included among the top collaborators of Daniel M. Gore 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 Daniel M. Gore. Daniel M. Gore is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Hau, Scott, Ismail Moghul, Shigeru Kanda, et al.. (2025). Current Applications of Artificial Intelligence for Fuchs Endothelial Corneal Dystrophy: A Systematic Review. Translational Vision Science & Technology. 14(6). 12–12. 1 indexed citations
2.
Gadhvi, Kunal A., Alfredo Borgia, Kirithika Muthusamy, et al.. (2024). Ablation Depth-Dependent Survival Analysis of Phototherapeutic Keratectomy for Recurrent Corneal Erosion Syndrome. Ophthalmology and Therapy. 14(1). 141–152.
3.
Li, Ji-Peng Olivia, Catey Bunce, Bruce Allan, et al.. (2024). A comparison of keratoconus progression following collagen cross-linkage using standard or personalised keratometry thresholds. Eye. 38(9). 1681–1686.
4.
Li, Ji-Peng Olivia, Mary D Fortune, Patrick Royston, et al.. (2022). Personalized Model to Predict Keratoconus Progression From Demographic, Topographic, and Genetic Data. American Journal of Ophthalmology. 240. 321–329. 10 indexed citations
5.
Li, Ji-Peng Olivia, Daniel M. Gore, Scott Hau, et al.. (2021). Machine Learning Algorithms to Detect Subclinical Keratoconus: Systematic Review. JMIR Medical Informatics. 9(12). e27363–e27363. 30 indexed citations
6.
Gadhvi, Kunal A., Vito Romano, Luis Fernández-Vega-Cueto, et al.. (2020). Femtosecond Laser–Assisted Deep Anterior Lamellar Keratoplasty for Keratoconus: Multi-surgeon Results. American Journal of Ophthalmology. 220. 191–202. 30 indexed citations
7.
Barrio, Jorge L. Alió del, Maninder Bhogal, Marcus Ang, et al.. (2020). Corneal transplantation after failed grafts: Options and outcomes. Survey of Ophthalmology. 66(1). 20–40. 36 indexed citations
8.
Gore, Daniel M., et al.. (2020). Accelerated Pulsed High-Fluence Corneal Cross-Linking for Progressive Keratoconus. American Journal of Ophthalmology. 221. 9–16. 23 indexed citations
9.
Fung, S., et al.. (2020). Technique for pediatric corneal crosslinking under general anesthesia. Journal of American Association for Pediatric Ophthalmology and Strabismus. 24(3). 162–164. 5 indexed citations
10.
Ferdi, Alex, Vuong Nguyen, Daniel M. Gore, et al.. (2019). Keratoconus Natural Progression. Ophthalmology. 126(7). 935–945. 164 indexed citations
11.
Quartilho, Ana, Daniel M. Gore, Catey Bunce, & Stephen J. Tuft. (2019). Royston−Parmar flexible parametric survival model to predict the probability of keratoconus progression to corneal transplantation. Eye. 34(4). 657–662. 5 indexed citations
12.
Khawaja, Anthony P., Karla E. Rojas López, Alison J. Hardcastle, et al.. (2019). Genetic Variants Associated With Corneal Biomechanical Properties and Potentially Conferring Susceptibility to Keratoconus in a Genome-Wide Association Study. JAMA Ophthalmology. 137(9). 1005–1005. 45 indexed citations
13.
Gore, Daniel M., et al.. (2018). Combined wavefront-guided transepithelial photorefractive keratectomy and corneal crosslinking for visual rehabilitation in moderate keratoconus. Journal of Cataract & Refractive Surgery. 44(5). 571–580. 35 indexed citations
14.
Gore, Daniel M., David O’Brart, P. M. W. French, Chris Dunsby, & Bruce Allan. (2015). Transepithelial Riboflavin Absorption in an Ex Vivo Rabbit Corneal Model. Investigative Ophthalmology & Visual Science. 56(8). 5006–5006. 32 indexed citations
15.
Gore, Daniel M., David O’Brart, P. M. W. French, Chris Dunsby, & Bruce Allan. (2015). A Comparison of Different Corneal Iontophoresis Protocols for Promoting Transepithelial Riboflavin Penetration. Investigative Ophthalmology & Visual Science. 56(13). 7908–7908. 31 indexed citations
16.
Gore, Daniel M., Anca Margineanu, P. M. W. French, et al.. (2014). Two-Photon Fluorescence Microscopy of Corneal Riboflavin Absorption. Investigative Ophthalmology & Visual Science. 55(4). 2476–2476. 25 indexed citations
17.
Watson, Martin, Seema Anand, Maninder Bhogal, et al.. (2013). Cataract surgery outcome in eyes with keratoconus. British Journal of Ophthalmology. 98(3). 361–364. 61 indexed citations
18.
Gore, Daniel M., Alex J. Shortt, & Bruce Allan. (2012). New clinical pathways for keratoconus. Eye. 27(3). 329–339. 59 indexed citations

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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