João M. Monteiro
- Artificial Intelligence
- Cognitive Neuroscience
- Health, Toxicology and Mutagenesis
- Radiology, Nuclear Medicine and Imaging
- Psychiatry and Mental health
- Co-authors
- Janaı́na Mourão-MirandaAnil RaoJoe TownsendJohn Shawe‐TaylorDale P. SandlerSudipto BanerjeeMark StenzelAaron Blair
- Topics
- Machine Learning in Healthcare (4 papers)Functional Brain Connectivity Studies (3 papers)Statistical Methods and Inference (2 papers)
- Journals
- NeuroImageIEEE Transactions on Neural Networks and Learning SystemsJournal of Neuroscience Methods
- Partner nations
- United KingdomUnited StatesItaly
In The Last Decade
João M. Monteiro
12 papers receiving 251 citations
Peers
Comparison fields: 5 of 92
- Artificial Intelligence 70
- Cognitive Neuroscience 65
- Health, Toxicology and Mutagenesis 44
- Radiology, Nuclear Medicine and Imaging 39
- Psychiatry and Mental health 19
Countries citing papers authored by João M. Monteiro
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
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
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | 15 | |
| 3 | 58 | |
| 4 | 4 | |
| 5 | 60 | |
| 6 | 33 | |
| 7 | 1 | |
| 8 | 13 | |
| 9 | 2 | |
| 10 | 3 | |
| 11 | 57 | |
| 12 | Can we interpret linear kernel machine learning models using anatomically labelled regions | 4 |
About João M. Monteiro
João M. Monteiro is a scholar working on Chemical Health and Safety, Health Informatics and Statistics and Probability, having authored 12 papers that have together received 261 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (4 papers), Functional Brain Connectivity Studies (3 papers) and Statistical Methods and Inference (2 papers). The work is most often cited by research in Health Informatics (9 citations), Chemical Health and Safety (3 citations) and Cognitive Neuroscience (65 citations). João M. Monteiro has collaborated with scholars based in United Kingdom, United States and Italy. Frequent co-authors include Janaı́na Mourão-Miranda, Anil Rao, Joe Townsend, John Shawe‐Taylor, Dale P. Sandler, Sudipto Banerjee, Mark Stenzel, Aaron Blair, Tran Huynh and Gurumurthy Ramachandran. Their work appears in journals such as NeuroImage, IEEE Transactions on Neural Networks and Learning Systems and Journal of Neuroscience Methods.
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.