João M. Monteiro

465 total citations
12 papers, 261 citations indexed

About

João M. Monteiro is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Computer Vision and Pattern Recognition. According to data from OpenAlex, João M. Monteiro has authored 12 papers receiving a total of 261 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 3 papers in Cognitive Neuroscience and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in João M. Monteiro's work include Machine Learning in Healthcare (4 papers), Functional Brain Connectivity Studies (3 papers) and Statistical Methods and Inference (2 papers). João M. Monteiro is often cited by papers focused on Machine Learning in Healthcare (4 papers), Functional Brain Connectivity Studies (3 papers) and Statistical Methods and Inference (2 papers). João M. Monteiro collaborates with scholars based in United Kingdom, United States and Italy. João M. Monteiro's co-authors include Janaı́na Mourão-Miranda, Anil Rao, Joe Townsend, John Shawe‐Taylor, Gurumurthy Ramachandran, Mark Stenzel, Patricia A. Stewart, Sudipto Banerjee, Dale P. Sandler and Lawrence S. Engel and has published in prestigious journals such as NeuroImage, IEEE Transactions on Neural Networks and Learning Systems and Journal of Neuroscience Methods.

In The Last Decade

João M. Monteiro

12 papers receiving 251 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
João M. Monteiro United Kingdom	7	70	65	44	39	19	12	261
José M. Sánchez United States	14	61 0.9×	37 0.6×	19 0.4×	132 3.4×	7 0.4×	31	1.2k
Nikki Marinsek United States	4	76 1.1×	20 0.3×	8 0.2×	36 0.9×	25 1.3×	5	245
Huitong Ding United States	8	97 1.4×	26 0.4×	19 0.4×	27 0.7×	82 4.3×	33	282
Saeed Arif Shah Pakistan	9	107 1.5×	59 0.9×	9 0.2×	36 0.9×	58 3.1×	26	372
Colin Birkenbihl Germany	12	76 1.1×	26 0.4×	37 0.8×	26 0.7×	79 4.2×	21	272
Noah Zimmerman United States	8	20 0.3×	21 0.3×	13 0.3×	13 0.3×	16 0.8×	12	283
Vladimir Kurbalija Serbia	11	183 2.6×	34 0.5×	11 0.3×	16 0.4×	29 1.5×	35	408
Andrada E. Ivanescu United States	10	46 0.7×	32 0.5×	9 0.2×	17 0.4×	19 1.0×	19	467
Liyuan Xu China	11	38 0.5×	34 0.5×	11 0.3×	9 0.2×	15 0.8×	42	351

Countries citing papers authored by João M. Monteiro

Since Specialization

Citations

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

Fields of papers citing papers by João M. Monteiro

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of João M. Monteiro

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

All Works

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12 of 12 papers shown

Secemsky, Eric A., Lindsay Bockstedt, Marc P. Bonaca, et al.. (2021). Long-term safety of drug-coated devices for peripheral revascularisation. EuroIntervention. 17(7). 590–598. 11 indexed citations

Donini, Michele, João M. Monteiro, Massimiliano Pontil, et al.. (2019). Combining heterogeneous data sources for neuroimaging based diagnosis: re-weighting and selecting what is important. NeuroImage. 195. 215–231. 15 indexed citations

Townsend, Joe, et al.. (2019). Extracting Relational Explanations From Deep Neural Networks: A Survey From a Neural-Symbolic Perspective. IEEE Transactions on Neural Networks and Learning Systems. 31(9). 3456–3470. 58 indexed citations

Monteiro, João M. & Carla Teixeira Lopes. (2018). HealthTalks - A Mobile App to Improve Health Communication and Personal Information Management. 329–332. 4 indexed citations

Rao, Anil, João M. Monteiro, & Janaı́na Mourão-Miranda. (2017). Predictive modelling using neuroimaging data in the presence of confounds. NeuroImage. 150. 23–49. 60 indexed citations

Rao, Anil, João M. Monteiro, & Janaı́na Mourão-Miranda. (2016). Prediction of clinical scores from neuroimaging data with censored likelihood gaussian processes. 1–4. 1 indexed citations

Monteiro, João M., Anil Rao, John Shawe‐Taylor, & Janaı́na Mourão-Miranda. (2016). A multiple hold-out framework for Sparse Partial Least Squares. Journal of Neuroscience Methods. 271. 182–194. 33 indexed citations

Donini, Michele, João M. Monteiro, Massimiliano Pontil, John Shawe‐Taylor, & Janaı́na Mourão-Miranda. (2016). A multimodal multiple kernel learning approach to Alzheimer's disease detection. 1–6. 13 indexed citations

Monteiro, João M., Anil Rao, John Ashburner, John Shawe‐Taylor, & Janaı́na Mourão-Miranda. (2015). Multivariate Effect Ranking via Adaptive Sparse PLS. 25–28. 3 indexed citations

10.

Rao, Anil, João M. Monteiro, John Ashburner, et al.. (2015). A Comparison of Strategies for Incorporating Nuisance Variables into Predictive Neuroimaging Models. 61–64. 2 indexed citations

11.

Huynh, Tran, Gurumurthy Ramachandran, Sudipto Banerjee, et al.. (2014). Comparison of Methods for Analyzing Left-Censored Occupational Exposure Data. The Annals of Occupational Hygiene. 58(9). 1126–42. 57 indexed citations

12.

Schrouff, Jessica, João M. Monteiro, Maria João Rosa, et al.. (2014). Can we interpret linear kernel machine learning models using anatomically labelled regions. Open Repository and Bibliography (University of Liège). 4 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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