H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 48 Citations 59,812 217 World Ranking 3113 National Ranking 65

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Machine learning

Bertrand Thirion mainly focuses on Artificial intelligence, Pattern recognition, Data mining, Brain mapping and Neuroimaging. His Artificial intelligence research integrates issues from Machine learning and Functional magnetic resonance imaging. His work carried out in the field of Pattern recognition brings together such families of science as Parametric statistics, Regularization, Total variation denoising, Multivariate statistics and Voxel.

Bertrand Thirion works mostly in the field of Multivariate statistics, limiting it down to topics relating to Dimensionality reduction and, in certain cases, Brain-reading. His Data mining research is multidisciplinary, incorporating perspectives in Covariance, Preprocessor, Volume and Outlier. His research integrates issues of Smoothing, Context, Overfitting and Cortical surface in his study of Neuroimaging.

His most cited work include:

  • Fast reproducible identification and large-scale databasing of individual functional cognitive networks. (125 citations)
  • Robust clustering of massive tractography datasets. (106 citations)
  • A supervised clustering approach for fMRI-based inference of brain states (102 citations)

What are the main themes of his work throughout his whole career to date?

Bertrand Thirion focuses on Artificial intelligence, Pattern recognition, Machine learning, Neuroimaging and Functional magnetic resonance imaging. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Data mining and Computer vision. His work is dedicated to discovering how Data mining, Estimator are connected with Anomaly detection and Covariance and other disciplines.

In Pattern recognition, Bertrand Thirion works on issues like Multivariate statistics, which are connected to Imaging genetics. His Machine learning study also includes

  • Brain mapping which intersects with area such as Cognition,
  • Resting state fMRI together with Connectome. His Feature selection study integrates concerns from other disciplines, such as Univariate and Dimensionality reduction.

He most often published in these fields:

  • Artificial intelligence (75.40%)
  • Pattern recognition (48.13%)
  • Machine learning (32.09%)

What were the highlights of his more recent work (between 2017-2021)?

  • Artificial intelligence (75.40%)
  • Cognition (11.76%)
  • Neuroimaging (28.34%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Artificial intelligence, Cognition, Neuroimaging, Inference and Functional magnetic resonance imaging. The study incorporates disciplines such as Machine learning, Linear model and Pattern recognition in addition to Artificial intelligence. Bertrand Thirion has included themes like Estimator and Lasso in his Pattern recognition study.

His work deals with themes such as Schizophrenia, Brain activity and meditation, Brain mapping and Developmental psychology, which intersect with Cognition. His Neuroimaging research incorporates elements of Field, Pipeline, Default mode network, Workflow and Cohort. His Inference research is multidisciplinary, incorporating elements of Smoothing, Set and Multivariate statistics.

Between 2017 and 2021, his most popular works were:

  • Benchmarking functional connectome-based predictive models for resting-state fMRI. (85 citations)
  • Subspecialization within default mode nodes characterized in 10,000 UK Biobank participants. (67 citations)
  • Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping. (48 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Artificial intelligence
  • Machine learning

Bertrand Thirion mainly investigates Neuroimaging, Cognition, Functional magnetic resonance imaging, Default mode network and Brain mapping. His studies deal with areas such as Variation, Field, Pipeline, Workflow and Data science as well as Neuroimaging. His work carried out in the field of Cognition brings together such families of science as Developmental psychology, Inference and Schizophrenia.

His Functional magnetic resonance imaging research integrates issues from Cognitive psychology, Categorical variable, Autism spectrum disorder, Neuropathology and Attention deficit hyperactivity disorder. His biological study spans a wide range of topics, including Precuneus, Fiber tract and Population variability. His Brain mapping study combines topics in areas such as Functional neuroimaging, Cognitive science, Cognitive neuroscience, Brain activity and meditation and Neural substrate.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Scikit-learn: Machine Learning in Python

Fabian Pedregosa;Gaël Varoquaux;Alexandre Gramfort;Vincent Michel.
Journal of Machine Learning Research (2011)

40587 Citations

Scikit-learn: Machine Learning in Python

Fabian Pedregosa;Gaël Varoquaux;Alexandre Gramfort;Vincent Michel.
arXiv: Learning (2012)

5180 Citations

Machine learning for neuroimaging with scikit-learn.

Alexandre Abraham;Alexandre Abraham;Fabian Pedregosa;Fabian Pedregosa;Michael Eickenberg;Michael Eickenberg;Philippe Gervais;Philippe Gervais.
Frontiers in Neuroinformatics (2014)

741 Citations

Analysis of a large fMRI cohort: Statistical and methodological issues for group analyses.

Bertrand Thirion;Philippe Pinel;Sébastien Mériaux;Alexis Roche.
NeuroImage (2007)

527 Citations

Recruitment of an Area Involved in Eye Movements During Mental Arithmetic

André Knops;André Knops;André Knops;Bertrand Thirion;Bertrand Thirion;Edward M. Hubbard;Edward M. Hubbard;Edward M. Hubbard;Vincent Michel;Vincent Michel;Vincent Michel.
Science (2009)

466 Citations

An automatic valuation system in the human brain: evidence from functional neuroimaging.

Maël Lebreton;Maël Lebreton;Soledad Jorge;Soledad Jorge;Vincent Michel;Bertrand Thirion.
Neuron (2009)

424 Citations

Assessing and tuning brain decoders: cross-validation, caveats, and guidelines

Gaël Varoquaux;Pradeep Reddy Raamana;Denis A. Engemann;Andrés Hoyos-Idrobo.
NeuroImage (2017)

338 Citations

Best practices in data analysis and sharing in neuroimaging using MRI.

Thomas E Nichols;Samir Das;Samir Das;Simon B Eickhoff;Simon B Eickhoff;Alan C Evans;Alan C Evans.
Nature Neuroscience (2017)

332 Citations

Inverse retinotopy: inferring the visual content of images from brain activation patterns.

Bertrand Thirion;Edouard Duchesnay;Edward M. Hubbard;Jessica Dubois.
NeuroImage (2006)

331 Citations

Deriving reproducible biomarkers from multi-site resting-state data: An Autism-based example

Alexandre Abraham;Michael P. Milham;Adriana Di Martino;R. Cameron Craddock.
NeuroImage (2017)

324 Citations

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