Akram Belghith

3.7k total citations · 3 hit papers
87 papers, 2.7k citations indexed

About

Akram Belghith is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Biomedical Engineering. According to data from OpenAlex, Akram Belghith has authored 87 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 74 papers in Radiology, Nuclear Medicine and Imaging, 72 papers in Ophthalmology and 9 papers in Biomedical Engineering. Recurrent topics in Akram Belghith's work include Glaucoma and retinal disorders (69 papers), Retinal Imaging and Analysis (59 papers) and Retinal Diseases and Treatments (47 papers). Akram Belghith is often cited by papers focused on Glaucoma and retinal disorders (69 papers), Retinal Imaging and Analysis (59 papers) and Retinal Diseases and Treatments (47 papers). Akram Belghith collaborates with scholars based in United States, Germany and South Korea. Akram Belghith's co-authors include Linda M. Zangwill, Robert N. Weinreb, Felipe A. Medeiros, Christopher Bowd, Luke J. Saunders, Min Hee Suh, Adeleh Yarmohammadi, Patricia Isabel C. Manalastas, Alberto Diniz‐Filho and Siamak Yousefi and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Akram Belghith

81 papers receiving 2.7k citations

Hit Papers

Optical Coherence Tomography Angiography Vessel Density i... 2016 2026 2019 2022 2016 2016 2018 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Akram Belghith United States 24 2.5k 2.3k 244 170 85 87 2.7k
Siamak Yousefi United States 22 1.7k 0.7× 1.7k 0.8× 124 0.5× 205 1.2× 46 0.5× 85 2.1k
Koenraad A. Vermeer Netherlands 23 1.3k 0.5× 1.4k 0.6× 826 3.4× 250 1.5× 80 0.9× 98 2.0k
Tin A. Tun Singapore 24 1.5k 0.6× 1.3k 0.6× 358 1.5× 81 0.5× 52 0.6× 92 1.7k
Mark Christopher United States 18 1.1k 0.4× 1.1k 0.5× 95 0.4× 140 0.8× 80 0.9× 55 1.3k
Hitoshi Tabuchi Japan 27 1.6k 0.7× 1.5k 0.6× 121 0.5× 69 0.4× 78 0.9× 156 2.0k
Martin F. Kraus United States 19 2.1k 0.8× 1.8k 0.8× 901 3.7× 96 0.6× 129 1.5× 35 2.6k
Stephanie J. Chiu United States 25 2.4k 1.0× 2.6k 1.1× 1.0k 4.1× 306 1.8× 341 4.0× 53 3.2k
Ce Zheng China 18 1.2k 0.5× 1.1k 0.5× 282 1.2× 130 0.8× 45 0.5× 49 1.3k
Kyungmoo Lee United States 22 1.5k 0.6× 1.5k 0.7× 648 2.7× 232 1.4× 145 1.7× 60 1.9k
Massimo A. Fazio United States 20 1.4k 0.6× 1.3k 0.6× 103 0.4× 71 0.4× 92 1.1× 100 1.6k

Countries citing papers authored by Akram Belghith

Since Specialization
Citations

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

Fields of papers citing papers by Akram Belghith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Akram Belghith. 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 Akram Belghith. The network helps show where Akram Belghith may publish in the future.

Co-authorship network of co-authors of Akram Belghith

This figure shows the co-authorship network connecting the top 25 collaborators of Akram Belghith. A scholar is included among the top collaborators of Akram Belghith 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 Akram Belghith. Akram Belghith 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.
Walker, Evan Harris, Christopher Bowd, Akram Belghith, et al.. (2025). Performance of General-Purpose Vision Language Models and Ophthalmology Foundation Models in Glaucoma Detection and Function Prediction. Translational Vision Science & Technology. 14(11). 31–31.
2.
Bowd, Christopher, Akram Belghith, Michael H. Goldbaum, et al.. (2025). Deep Learning Approach Predicts Longitudinal Retinal Nerve Fiber Layer Thickness Changes. Bioengineering. 12(2). 139–139.
3.
Bowd, Christopher, Jasmin Rezapour, Akram Belghith, et al.. (2024). Deep Learning Identifies High-Quality Fundus Photographs and Increases Accuracy in Automated Primary Open Angle Glaucoma Detection. Translational Vision Science & Technology. 13(1). 23–23. 8 indexed citations
4.
Belghith, Akram, Jasmin Rezapour, Eleonora Micheletti, et al.. (2024). Rates of Choriocapillaris Microvascular Dropout and Macular Structural Changes in Glaucomatous Optic Neuropathy With and Without Myopia. American Journal of Ophthalmology. 267. 257–270. 1 indexed citations
5.
Rezapour, Jasmin, Akram Belghith, Christopher Bowd, et al.. (2024). Diagnostic Accuracy of Optic Nerve Head and Macula OCT Parameters for Detecting Glaucoma in Eyes With and Without High Axial Myopia. American Journal of Ophthalmology. 266. 77–91. 5 indexed citations
6.
Bowd, Christopher, Akram Belghith, Jasmin Rezapour, et al.. (2024). Wide-Field Optical Coherence Tomography Imaging Improves Rate of Change Detection in Progressing Glaucomatous Eyes Compared With Standard-Field Imaging. Investigative Ophthalmology & Visual Science. 65(8). 18–18.
7.
Christopher, Mark, Rubèn González, Bharanidharan Radha Saseendrakumar, et al.. (2024). Proactive Decision Support for Glaucoma Treatment: Predicting Surgical Interventions with Clinically Available Data. Bioengineering. 11(2). 140–140. 7 indexed citations
8.
Bowd, Christopher, Akram Belghith, Michael H. Goldbaum, et al.. (2024). Glaucoma Detection and Feature Identification via GPT-4V Fundus Image Analysis. SHILAP Revista de lepidopterología. 5(2). 100667–100667. 3 indexed citations
9.
Micheletti, Eleonora, Nevin W. El-Nimri, Takashi Nishida, et al.. (2023). Central visual field damage in glaucoma eyes with choroidal microvasculature dropout with and without high axial myopia. British Journal of Ophthalmology. 108(3). 372–379. 8 indexed citations
10.
Rezapour, Jasmin, Christopher Bowd, Akram Belghith, et al.. (2022). Macula structural and vascular differences in glaucoma eyes with and without high axial myopia. British Journal of Ophthalmology. 107(9). 1286–1294. 15 indexed citations
11.
Fan, Rui, Christopher Bowd, Mark Christopher, et al.. (2022). Detecting Glaucoma from Fundus Photographs Using Deep Learning without Convolutions. SHILAP Revista de lepidopterología. 3(1). 100233–100233. 74 indexed citations
12.
Rezapour, Jasmin, James A. Proudfoot, Christopher Bowd, et al.. (2021). Bruch Membrane Opening Detection Accuracy in Healthy Eyes and Eyes With Glaucoma With and Without Axial High Myopia in an American and Korean Cohort. American Journal of Ophthalmology. 237. 221–234. 17 indexed citations
13.
Christopher, Mark, Christopher Bowd, James A. Proudfoot, et al.. (2021). Performance of Deep Learning Models to Detect Glaucoma Using Unsegmented Radial and Circle OCT Scans of the Optic Nerve Head. Investigative Ophthalmology & Visual Science. 62(8). 1014–1014. 1 indexed citations
14.
Rezapour, Jasmin, Christopher Bowd, Akram Belghith, et al.. (2021). Macular thickness and vessel density in glaucoma eyes with and without high axial myopia. Investigative Ophthalmology & Visual Science. 62(8). 2431–2431. 1 indexed citations
15.
Christopher, Mark, Christopher Bowd, Akram Belghith, et al.. (2020). Deep Learning Models Based on Unsegmented OCT RNFL Circle Scans Provide Accurate Detection of Glaucoma and High Resolution Prediction of Visual Field Damage. Investigative Ophthalmology & Visual Science. 61(7). 1439–1439. 2 indexed citations
16.
Yarmohammadi, Adeleh, Linda M. Zangwill, Alberto Diniz‐Filho, et al.. (2016). OCT Angiography Vessel Density in Normal, Glaucoma Suspects and Glaucoma Eyes: Structural and Functional Associations in the Diagnostic Innovations in Glaucoma Study (DIGS). Investigative Ophthalmology & Visual Science. 57(12). 2958–2958. 5 indexed citations
17.
Hammel, Naama, Akram Belghith, Felipe A. Medeiros, et al.. (2016). Diagnostic Innovations in Glaucoma Study (DIGS): Comparing the Rates of Macular Ganglion Cell layer loss in Healthy, non-progressing Glaucoma and progressing glaucoma Eyes. Investigative Ophthalmology & Visual Science. 57(12). 373–373. 2 indexed citations
18.
Belghith, Akram, Siamak Yousefi, Jameson Merkow, et al.. (2016). Diabetic retinopathy detection from image to classification using deep convolutional neural network. Investigative Ophthalmology & Visual Science. 57(12). 5961–5961. 3 indexed citations
19.
Suh, Min Hee, Linda M. Zangwill, Patricia Isabel C. Manalastas, et al.. (2016). Deep Retinal Layer Microvasculature Dropout Detected by the Optical Coherence Tomography Angiography in Glaucoma. Ophthalmology. 123(12). 2509–2518. 188 indexed citations
20.
Hammel, Naama, Akram Belghith, Felipe A. Medeiros, et al.. (2015). Diagnostic Innovations in Glaucoma Study (DIGS): Comparing the Rates of Peripapillary Retinal Nerve Fiber layer and Ganglion Cell-Inner Plexiform Layer Loss in Healthy and Glaucoma Eyes. Investigative Ophthalmology & Visual Science. 56(7). 4568–4568. 1 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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