M. López

2.6k total citations
42 papers, 1.7k citations indexed

About

M. López is a scholar working on Computer Vision and Pattern Recognition, Neurology and Physiology. According to data from OpenAlex, M. López has authored 42 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Computer Vision and Pattern Recognition, 16 papers in Neurology and 9 papers in Physiology. Recurrent topics in M. López's work include Image Retrieval and Classification Techniques (18 papers), Brain Tumor Detection and Classification (15 papers) and Face and Expression Recognition (11 papers). M. López is often cited by papers focused on Image Retrieval and Classification Techniques (18 papers), Brain Tumor Detection and Classification (15 papers) and Face and Expression Recognition (11 papers). M. López collaborates with scholars based in Spain, Portugal and Germany. M. López's co-authors include Javier Ramı́rez, J. M. Górriz, D. Salas-González, I. Álvarez, F. Segovia, R. Chaves, Pablo Padilla, Carlos G. Puntonet, Manuel Gómez-Río and Isabella Castiglioni and has published in prestigious journals such as Expert Systems with Applications, IEEE Transactions on Medical Imaging and Information Sciences.

In The Last Decade

M. López

40 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
M. López Spain 22 591 562 387 367 334 42 1.7k
F. Segovia Spain 26 668 1.1× 621 1.1× 459 1.2× 461 1.3× 435 1.3× 82 2.0k
I. Álvarez Spain 30 714 1.2× 752 1.3× 515 1.3× 431 1.2× 422 1.3× 75 2.2k
D. Salas-González Spain 31 872 1.5× 983 1.7× 656 1.7× 398 1.1× 424 1.3× 92 2.5k
Iman Beheshti Canada 22 538 0.9× 257 0.5× 275 0.7× 635 1.7× 525 1.6× 63 1.7k
Francisco J. Martínez-Murcia Spain 21 314 0.5× 238 0.4× 264 0.7× 304 0.8× 183 0.5× 62 1.3k
R. Chaves Spain 15 400 0.7× 369 0.7× 280 0.7× 198 0.5× 246 0.7× 29 1.0k
Rémi Cuingnet France 12 579 1.0× 498 0.9× 278 0.7× 425 1.2× 669 2.0× 23 1.6k
Mingxia Liu China 19 452 0.8× 348 0.6× 430 1.1× 257 0.7× 249 0.7× 44 1.6k
Chong-Yaw Wee United States 24 362 0.6× 267 0.5× 289 0.7× 1.5k 4.0× 484 1.4× 37 2.3k
Ninon Burgos France 20 358 0.6× 291 0.5× 396 1.0× 205 0.6× 328 1.0× 56 1.7k

Countries citing papers authored by M. López

Since Specialization
Citations

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

Fields of papers citing papers by M. López

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. López

This figure shows the co-authorship network connecting the top 25 collaborators of M. López. A scholar is included among the top collaborators of M. López 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 M. López. M. López 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.
2.
López, M., et al.. (2023). New Nitric Oxide-Releasing Compounds as Promising Anti-Bladder Cancer Drugs. Biomedicines. 11(1). 199–199. 3 indexed citations
3.
Cruz, Esteban, et al.. (2014). Quedas: revisão de novos conceitos. 13(2). 5 indexed citations
4.
Hidalgo-Muñoz, Antonio R., M. López, Alejandro Galvao-Carmona, et al.. (2013). EEG study on affective valence elicited by novel and familiar pictures using ERD/ERS and SVM-RFE. Medical & Biological Engineering & Computing. 52(2). 149–158. 7 indexed citations
5.
Hidalgo-Muñoz, Antonio R., A.T. Pereira, M. López, et al.. (2013). Individual EEG differences in affective valence processing in women with low and high neuroticism. Clinical Neurophysiology. 124(9). 1798–1806. 5 indexed citations
6.
Salvatore, Christian, Antonio Cerasa, Isabella Castiglioni, et al.. (2013). Machine learning on brain MRI data for differential diagnosis of Parkinson's disease and Progressive Supranuclear Palsy. Journal of Neuroscience Methods. 222. 230–237. 201 indexed citations
7.
Padilla, Pablo, M. López, J. M. Górriz, et al.. (2011). NMF-SVM Based CAD Tool Applied to Functional Brain Images for the Diagnosis of Alzheimer's Disease. IEEE Transactions on Medical Imaging. 31(2). 207–216. 121 indexed citations
8.
Ramı́rez, Javier, J. M. Górriz, F. Segovia, et al.. (2010). Computer aided diagnosis system for the Alzheimer's disease based on partial least squares and random forest SPECT image classification. Neuroscience Letters. 472(2). 99–103. 98 indexed citations
9.
Padilla, Pablo, J. M. Górriz, Javier Ramı́rez, et al.. (2010). Analysis of SPECT brain images for the diagnosis of Alzheimer's disease based on NMF for feature extraction. Neuroscience Letters. 479(3). 192–196. 21 indexed citations
10.
Salas-González, D., J. M. Górriz, Javier Ramı́rez, et al.. (2010). Feature selection using factor analysis for Alzheimer's diagnosis using PET images. Medical Physics. 37(11). 6084–6095. 60 indexed citations
11.
Segovia, F., J. M. Górriz, Javier Ramı́rez, et al.. (2010). Classification of functional brain images using a GMM-based multi-variate approach. Neuroscience Letters. 474(1). 58–62. 33 indexed citations
12.
Salas-González, D., J. M. Górriz, Javier Ramı́rez, et al.. (2010). Computer-aided diagnosis of Alzheimer's disease using support vector machines and classification trees. Physics in Medicine and Biology. 55(10). 2807–2817. 44 indexed citations
13.
Álvarez, I., J. M. Górriz, Javier Ramı́rez, et al.. (2010). 18F-FDG PET imaging analysis for computer aided Alzheimer’s diagnosis. Information Sciences. 181(4). 903–916. 104 indexed citations
14.
Ramı́rez, Javier, J. M. Górriz, F. Segovia, et al.. (2010). Early Alzheimer's disease diagnosis using partial least squares and random forests. 3217. 81–84. 5 indexed citations
15.
López, M., Javier Ramı́rez, J. M. Górriz, et al.. (2009). SVM-based CAD system for early detection of the Alzheimer's disease using kernel PCA and LDA. Neuroscience Letters. 464(3). 233–238. 97 indexed citations
16.
Segovia, F., J. M. Górriz, Javier Ramı́rez, et al.. (2009). fMRI data analysis using a novel clustering technique. 45. 3399–3403. 2 indexed citations
17.
López, M., Javier Ramı́rez, J. M. Górriz, et al.. (2009). Neurological image classification for the Alzheimer's Disease diagnosis using Kernel PCA and Support Vector Machines. 1496. 2486–2489. 9 indexed citations
18.
Salas-González, D., J. M. Górriz, Javier Ramı́rez, et al.. (2009). Analysis of SPECT brain images for the diagnosis of Alzheimer's disease using moments and support vector machines. Neuroscience Letters. 461(1). 60–64. 33 indexed citations
19.
Chaves, R., Javier Ramı́rez, J. M. Górriz, et al.. (2009). SVM-based computer-aided diagnosis of the Alzheimer's disease using t-test NMSE feature selection with feature correlation weighting. Neuroscience Letters. 461(3). 293–297. 107 indexed citations
20.
López, M., Javier Ramı́rez, J. M. Górriz, et al.. (2009). Multivariate approaches for Alzheimer's disease diagnosis using Bayesian classifiers. 41. 3190–3193. 7 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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