Aaron Long

734 total citations · 1 hit paper
6 papers, 623 citations indexed

About

Aaron Long is a scholar working on Pulmonary and Respiratory Medicine, Artificial Intelligence and Media Technology. According to data from OpenAlex, Aaron Long has authored 6 papers receiving a total of 623 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Pulmonary and Respiratory Medicine, 2 papers in Artificial Intelligence and 2 papers in Media Technology. Recurrent topics in Aaron Long's work include AI in cancer detection (2 papers), Image Processing Techniques and Applications (2 papers) and Digital Radiography and Breast Imaging (2 papers). Aaron Long is often cited by papers focused on AI in cancer detection (2 papers), Image Processing Techniques and Applications (2 papers) and Digital Radiography and Breast Imaging (2 papers). Aaron Long collaborates with scholars based in United States, Mexico and Japan. Aaron Long's co-authors include Mauricio Terrones, Ana Laura Elías, Luis Balicas, Humberto Terrones, Nihar Pradhan, Néstor Perea‐López, Simin Feng, Ruitao Lv, Yoong Ahm Kim and Morinobu Endo and has published in prestigious journals such as ACS Nano, Pediatric Radiology and Radiology Artificial Intelligence.

In The Last Decade

Aaron Long

6 papers receiving 610 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Controlled Synthesis and Transfer of Large-Area WS₂ Sheets: From Single Layer to Few Layers

2013 537 citations Ana Laura Elías, Néstor Perea‐López et al. ACS Nano profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Aaron Long United States	4	493	264	73	60	51	6	623
Seung Hee Choi South Korea	13	340 0.7×	418 1.6×	22 0.3×	57 0.9×	27 0.5×	38	571
Giulio Benetti Italy	12	198 0.4×	57 0.2×	37 0.5×	129 2.1×	61 1.2×	17	357
Jichun Li China	14	164 0.3×	253 1.0×	28 0.4×	155 2.6×	36 0.7×	32	535
Merfat Algethami Saudi Arabia	13	300 0.6×	89 0.3×	14 0.2×	78 1.3×	50 1.0×	41	527
Jiancui Chen China	15	572 1.2×	421 1.6×	38 0.5×	111 1.9×	8 0.2×	31	769
Krishna V. Singh United States	9	226 0.5×	96 0.4×	31 0.4×	102 1.7×	21 0.4×	12	384
Guowei Chen China	11	453 0.9×	348 1.3×	12 0.2×	41 0.7×	13 0.3×	42	715
Henry Yu United States	13	365 0.7×	153 0.6×	34 0.5×	91 1.5×	16 0.3×	36	608
Saeed Ahmad Buzdar Pakistan	12	179 0.4×	105 0.4×	50 0.7×	82 1.4×	83 1.6×	63	452
Yu Dian Lim Singapore	11	160 0.3×	154 0.6×	7 0.1×	68 1.1×	26 0.5×	50	409

Countries citing papers authored by Aaron Long

Since Specialization

Citations

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

Fields of papers citing papers by Aaron Long

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aaron Long

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

All Works

Sort: Min cites: Since: Top N: Style:

6 of 6 papers shown

1.

Singh, Sadanand, et al.. (2020). Adaptation of a deep learning malignancy model from full-field digital mammography to digital breast tomosynthesis. 5–5. 11 indexed citations

2.

Matthews, Thomas P., Sadanand Singh, Jason Su, et al.. (2020). A Multisite Study of a Breast Density Deep Learning Model for Full-Field Digital Mammography and Synthetic Mammography. Radiology Artificial Intelligence. 3(1). e200015–e200015. 28 indexed citations

3.

Moore, Michael M., Einat Slonimsky, Aaron Long, Raymond W. Sze, & Ramesh S. Iyer. (2019). Machine learning concepts, concerns and opportunities for a pediatric radiologist. Pediatric Radiology. 49(4). 509–516. 42 indexed citations

4.

Long, Aaron, et al.. (2017). Foveal scale space generation with the log-polar transform. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 10209. 1020910–1020910. 2 indexed citations

5.

Long, Aaron, et al.. (2016). Analysis and implementation of the foveated vision of the raptor eye. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9854. 98540T–98540T. 3 indexed citations

6.

Elías, Ana Laura, Néstor Perea‐López, Andrés Castro-Beltrán, et al.. (2013). Controlled Synthesis and Transfer of Large-Area WS₂ Sheets: From Single Layer to Few Layers. ACS Nano. 7(6). 5235–5242. 537 indexed citations breakdown →

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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