Alex Leow

8.6k total citations · 1 hit paper
168 papers, 5.4k citations indexed

About

Alex Leow is a scholar working on Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience and Experimental and Cognitive Psychology. According to data from OpenAlex, Alex Leow has authored 168 papers receiving a total of 5.4k indexed citations (citations by other indexed papers that have themselves been cited), including 77 papers in Radiology, Nuclear Medicine and Imaging, 69 papers in Cognitive Neuroscience and 38 papers in Experimental and Cognitive Psychology. Recurrent topics in Alex Leow's work include Advanced Neuroimaging Techniques and Applications (69 papers), Functional Brain Connectivity Studies (61 papers) and Mental Health Research Topics (34 papers). Alex Leow is often cited by papers focused on Advanced Neuroimaging Techniques and Applications (69 papers), Functional Brain Connectivity Studies (61 papers) and Mental Health Research Topics (34 papers). Alex Leow collaborates with scholars based in United States, Australia and China. Alex Leow's co-authors include Paul M. Thompson, Arthur W. Toga, Xue Hua, Olusola Ajilore, Liang Zhan, James T. Becker, Neelroop Parikshak, Michael W. Weiner, Clifford R. Jack and April J. Ho and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and SHILAP Revista de lepidopterología.

In The Last Decade

Alex Leow

159 papers receiving 5.3k citations

Hit Papers

Brain structure and obesity 2009 2026 2014 2020 2009 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alex Leow United States 39 2.1k 2.0k 1.4k 1.0k 594 168 5.4k
Albert Montillo United States 19 3.6k 1.7× 2.6k 1.3× 1.9k 1.3× 911 0.9× 515 0.9× 59 7.6k
Christian Haselgrove United States 13 4.1k 1.9× 2.6k 1.3× 2.2k 1.5× 973 0.9× 517 0.9× 32 7.9k
Greig I. de Zubicaray Australia 50 5.2k 2.5× 3.0k 1.5× 1.6k 1.1× 1.0k 1.0× 923 1.6× 259 8.4k
Susana Muñoz Maniega United Kingdom 41 1.9k 0.9× 2.4k 1.2× 1.6k 1.1× 748 0.7× 387 0.7× 125 6.6k
Noor Jehan Kabani Canada 19 2.6k 1.2× 2.0k 1.0× 1.0k 0.7× 480 0.5× 387 0.7× 21 6.0k
Susanne G. Mueller United States 33 2.1k 1.0× 1.7k 0.9× 2.3k 1.6× 1.4k 1.4× 184 0.3× 66 5.2k
Ivo D. Dinov United States 46 1.9k 0.9× 1.8k 0.9× 1.4k 0.9× 1.0k 1.0× 202 0.3× 197 7.2k
Neda Jahanshad United States 41 2.3k 1.1× 2.3k 1.2× 855 0.6× 652 0.6× 316 0.5× 275 5.2k
Dominic Holland United States 42 2.4k 1.2× 1.7k 0.9× 2.2k 1.5× 1.6k 1.5× 314 0.5× 76 6.3k
Dorothee P. Auer United Kingdom 58 3.3k 1.6× 3.1k 1.6× 1.1k 0.8× 1.0k 1.0× 706 1.2× 271 11.1k

Countries citing papers authored by Alex Leow

Since Specialization
Citations

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

Fields of papers citing papers by Alex Leow

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alex Leow

This figure shows the co-authorship network connecting the top 25 collaborators of Alex Leow. A scholar is included among the top collaborators of Alex Leow 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 Alex Leow. Alex Leow 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
2.
Vaishnavi, Sandeep, et al.. (2025). Changes in Neural Activities and Neuroplasticity Related to Nonpharmacological Interventions for Major Depressive Disorder: A Systematic Literature Review. Biological Psychiatry Global Open Science. 5(6). 100572–100572. 1 indexed citations
4.
Estabrook, Ryne, John Zulueta, Scott A. Langenecker, et al.. (2025). Predicting cognitive functioning in mood disorders through smartphone typing dynamics.. Journal of Psychopathology and Clinical Science. 134(8). 998–1019.
5.
Eisenlohr‐Moul, Tory A., et al.. (2024). Smartphone keyboard dynamics predict affect in suicidal ideation. npj Digital Medicine. 7(1). 54–54. 5 indexed citations
6.
Shetti, Aashutosh, Wenping Li, Liang Zhan, et al.. (2024). Temporal Alterations in White Matter in AnAppKnock-In Mouse Model of Alzheimer’s Disease. eNeuro. 11(2). ENEURO.0496–23.2024. 3 indexed citations
7.
Ma, Guixiang, Yanfu Zhang, Kai Ye, et al.. (2023). A comprehensive survey of complex brain network representation. SHILAP Revista de lepidopterología. 1(3). 100046–100046. 13 indexed citations
8.
Bennett, Casey C., et al.. (2023). A Novel Approach to Clustering Accelerometer Data for Application in Passive Predictions of Changes in Depression Severity. Sensors. 23(3). 1585–1585. 10 indexed citations
9.
Peng, Hao, et al.. (2022). Federated Multi-view Learning for Private Medical Data Integration and Analysis. ACM Transactions on Intelligent Systems and Technology. 13(4). 1–23. 27 indexed citations
10.
Guo, Lei, Yalin Wang, Scott Mackin, et al.. (2022). Signed graph representation learning for functional-to-structural brain network mapping. Medical Image Analysis. 83. 102674–102674. 16 indexed citations
12.
Korthauer, Laura E., Liang Zhan, Olusola Ajilore, et al.. (2021). Inferring excitation-inhibition dynamics using a maximum entropy model unifying brain structure and function. Network Neuroscience. 6(2). 420–444. 8 indexed citations
13.
Ansari, Rashid, Ahmet Enis Çetin, Alex Leow, et al.. (2021). EEG Classification by Factoring in Sensor Spatial Configuration. IEEE Access. 9. 19053–19065. 22 indexed citations
14.
Feusner, Jamie D., et al.. (2021). Semantic Linkages of Obsessions From an International Obsessive-Compulsive Disorder Mobile App Data Set: Big Data Analytics Study. Journal of Medical Internet Research. 23(6). e25482–e25482. 7 indexed citations
15.
Hua, Xue, Christopher R. K. Ching, Adam Mezher, et al.. (2015). MRI-based brain atrophy rates in ADNI phase 2: acceleration and enrichment considerations for clinical trials. Neurobiology of Aging. 37. 26–37. 35 indexed citations
16.
Ajilore, Olusola, Nathalie Vizueta, Patricia D. Walshaw, et al.. (2015). Connectome signatures of neurocognitive abnormalities in euthymic bipolar I disorder. Journal of Psychiatric Research. 68. 37–44. 34 indexed citations
17.
Charlton, Rebecca A., Alex Leow, Johnson GadElkarim, et al.. (2014). Brain Connectivity in Late-Life Depression and Aging Revealed by Network Analysis. American Journal of Geriatric Psychiatry. 23(6). 642–650. 16 indexed citations
18.
Leow, Alex, Danielle Harvey, Naomi J. Goodrich‐Hunsaker, et al.. (2014). Altered structural brain connectome in young adult fragile X premutation carriers. Human Brain Mapping. 35(9). 4518–4530. 14 indexed citations
19.
Zhang, Aifeng, Alex Leow, Olusola Ajilore, et al.. (2011). Quantitative Tract-Specific Measures of Uncinate and Cingulum in Major Depression Using Diffusion Tensor Imaging. Neuropsychopharmacology. 37(4). 959–967. 107 indexed citations
20.
Thompson, Paul M., Elizabeth R. Sowell, Nitin Gogtay, et al.. (2005). Structural MRI and Brain Development. International review of neurobiology. 67. 285–323. 75 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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