Praveer Singh

4.0k total citations
58 papers, 1.3k citations indexed

About

Praveer Singh is a scholar working on Radiology, Nuclear Medicine and Imaging, Pediatrics, Perinatology and Child Health and Organic Chemistry. According to data from OpenAlex, Praveer Singh has authored 58 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Radiology, Nuclear Medicine and Imaging, 13 papers in Pediatrics, Perinatology and Child Health and 12 papers in Organic Chemistry. Recurrent topics in Praveer Singh's work include Retinopathy of Prematurity Studies (15 papers), Neonatal and fetal brain pathology (13 papers) and Retinal Imaging and Analysis (10 papers). Praveer Singh is often cited by papers focused on Retinopathy of Prematurity Studies (15 papers), Neonatal and fetal brain pathology (13 papers) and Retinal Imaging and Analysis (10 papers). Praveer Singh collaborates with scholars based in United States, India and France. Praveer Singh's co-authors include Nikos Komodakis, Jayashree Kalpathy–Cramer, Ken Chang, Matthew Li, Katharina Hoebel, J. Peter Campbell, Nishanth Arun, Mishka Gidwani, Michael F. Chiang and Sharut Gupta and has published in prestigious journals such as SHILAP Revista de lepidopterología, Nano Letters and PEDIATRICS.

In The Last Decade

Praveer Singh

49 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Praveer Singh United States 20 519 259 253 156 156 58 1.3k
Chung‐Ming Chen Taiwan 24 1.1k 2.1× 652 2.5× 452 1.8× 470 3.0× 68 0.4× 127 2.5k
Guangyi Wang China 21 536 1.0× 178 0.7× 158 0.6× 192 1.2× 15 0.1× 126 1.7k
Zhihao Wu China 9 429 0.8× 343 1.3× 341 1.3× 75 0.5× 30 0.2× 16 1.0k
Benzheng Wei China 17 1.1k 2.0× 853 3.3× 727 2.9× 83 0.5× 77 0.5× 74 1.9k
Gregor Urban United States 12 454 0.9× 381 1.5× 398 1.6× 219 1.4× 35 0.2× 24 1.6k
Feng Yang China 18 1.2k 2.2× 502 1.9× 546 2.2× 640 4.1× 124 0.8× 81 2.0k
Fei Shi China 27 1.6k 3.1× 460 1.8× 1.0k 4.1× 83 0.5× 200 1.3× 174 2.8k
Rizwan Qureshi Pakistan 18 168 0.3× 165 0.6× 174 0.7× 170 1.1× 59 0.4× 90 1.4k
Bo Zhou China 22 626 1.2× 162 0.6× 192 0.8× 105 0.7× 18 0.1× 131 1.6k
Minghui Wang China 18 366 0.7× 425 1.6× 401 1.6× 84 0.5× 214 1.4× 54 1.3k

Countries citing papers authored by Praveer Singh

Since Specialization
Citations

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

Fields of papers citing papers by Praveer Singh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Praveer Singh

This figure shows the co-authorship network connecting the top 25 collaborators of Praveer Singh. A scholar is included among the top collaborators of Praveer Singh 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 Praveer Singh. Praveer Singh 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.
Hallaj, Shahin, Praveer Singh, Jayashree Kalpathy–Cramer, et al.. (2024). Federated Learning in Glaucoma. Ophthalmology Glaucoma. 8(1). 92–105.
2.
Coyner, Aaron S., Parag K. Shah, Venkatapathy Narendran, et al.. (2023). Epidemiologic Evaluation of Retinopathy of Prematurity Severity in a Large Telemedicine Program in India Using Artificial Intelligence. Ophthalmology. 130(8). 837–843. 5 indexed citations
3.
Jordan, Brian K., Brian Scottoline, Susan Ostmo, et al.. (2023). Oxygenation Fluctuations Associated with Severe Retinopathy of Prematurity. SHILAP Revista de lepidopterología. 4(2). 100417–100417. 5 indexed citations
4.
Li, Matthew, Nishanth Arun, Mehak Aggarwal, et al.. (2022). Multi-population generalizability of a deep learning-based chest radiograph severity score for COVID-19. Medicine. 101(29). e29587–e29587. 10 indexed citations
5.
Cole, Emily, Nita Valikodath, Tala Al-Khaled, et al.. (2022). Evaluation of an Artificial Intelligence System for Retinopathy of Prematurity Screening in Nepal and Mongolia. SHILAP Revista de lepidopterología. 2(4). 100165–100165. 9 indexed citations
6.
Gidwani, Mishka, Ken Chang, Jay Patel, et al.. (2022). Inconsistent Partitioning and Unproductive Feature Associations Yield Idealized Radiomic Models. Radiology. 307(1). e220715–e220715. 21 indexed citations
7.
Arun, Nishanth, Nathan Gaw, Praveer Singh, et al.. (2021). Assessing the Trustworthiness of Saliency Maps for Localizing Abnormalities in Medical Imaging. Radiology Artificial Intelligence. 3(6). e200267–e200267. 147 indexed citations
8.
Singh, Praveer, J. Peter Campbell, Susan Ostmo, et al.. (2021). External validation of a deep learning algorithm for plus disease classification on a multinational ROP dataset. Investigative Ophthalmology & Visual Science. 62(8). 3266–3266.
9.
Coyner, Aaron S., Jayashree Kalpathy–Cramer, Jimmy Chen, et al.. (2021). A risk model for early detection of treatment-requiring retinopathy of prematurity using a deep learning-derived vascular severity score. Investigative Ophthalmology & Visual Science. 62(8). 3265–3265. 1 indexed citations
10.
Arun, Nishanth, Praveer Singh, Jiali Wang, et al.. (2021). Automated detection of genetic relatedness from fundus photographs using Convolutional Siamese Neural Networks. Investigative Ophthalmology & Visual Science. 62(8). 1034–1034. 1 indexed citations
11.
Chen, Jimmy, Aaron S. Coyner, Susan Ostmo, et al.. (2021). Deep Learning for the Diagnosis of Stage in Retinopathy of Prematurity. Ophthalmology Retina. 5(10). 1027–1035. 40 indexed citations
12.
Valikodath, Nita, Emily Cole, Tala Al-Khaled, et al.. (2020). Utility of an automated deep learning tool in a low-income country for retinopathy of prematurity. Investigative Ophthalmology & Visual Science. 61(7). 1637–1637. 1 indexed citations
13.
Li, Matthew, Nishanth Arun, Mishka Gidwani, et al.. (2020). Automated Assessment and Tracking of COVID-19 Pulmonary Disease Severity on Chest Radiographs Using Convolutional Siamese Neural Networks. Radiology Artificial Intelligence. 2(4). e200079–e200079. 105 indexed citations
14.
Coyner, Aaron S., J. Peter Campbell, Jayashree Kalpathy–Cramer, et al.. (2020). Retinal Fundus Image Generation in Retinopathy of Prematurity Using Autoregressive Generative Models. Investigative Ophthalmology & Visual Science. 61(7). 2166–2166. 2 indexed citations
15.
Chang, Ken, Andrew Beers, Jay Patel, et al.. (2020). Multi-Institutional Assessment and Crowdsourcing Evaluation of Deep Learning for Automated Classification of Breast Density. Journal of the American College of Radiology. 17(12). 1653–1662. 37 indexed citations
16.
Campbell, J. Peter, Robison Vernon Paul Chan, Susan Ostmo, et al.. (2020). Analysis of the relationship between retinopathy of prematurity zone, stage, extent and a deep learning-based vascular severity scale. 61(7). 2193–2193. 2 indexed citations
17.
Loupos, Konstantinos, Anastasios Doulamis, Christos Stentoumis, et al.. (2017). Autonomous robotic system for tunnel structural inspection and assessment. International Journal of Intelligent Robotics and Applications. 2(1). 43–66. 75 indexed citations
18.
Sethi, Arun, et al.. (2016). Synthesis of novel pregnane-diosgenin prodrugs via Ring A and Ring A connection: A combined experimental and theoretical studies. Journal of Molecular Structure. 1125. 616–623. 24 indexed citations
19.
Siddiqui, Shamoon Ahmad, Praveer Singh, Sudha Jain, et al.. (2009). VIBRATIONAL DYNAMICS AND POTENTIAL ENERGY DISTRIBUTION OF TWO WELL-KNOWN NEUROTRANSMITTER RECEPTORS: TYRAMINE AND DOPAMINE HYDROCHLORIDE. Journal of Theoretical and Computational Chemistry. 8(3). 433–450. 32 indexed citations
20.
Singh, Praveer, et al.. (2007). Vibrational dynamics of the organometallic compound triarylorganoantimony (V) SbPh3[O2CC(OH)Ph2]2. Pramana. 68(5). 875–881. 2 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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