D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Neuroscience D-index 30 Citations 3,689 67 World Ranking 5632 National Ranking 174

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Neuroscience
  • Artificial intelligence

His primary scientific interests are in Artificial intelligence, Resting state fMRI, Neuroscience, Causal model and Bayesian inference. Artificial intelligence is often connected to Dynamic causal modelling in his work. His work carried out in the field of Resting state fMRI brings together such families of science as Cognition, Default mode network and Brain mapping.

His work in the fields of Resting fmri and Functional connectivity overlaps with other areas such as Rest and Event. As part of one scientific family, he deals mainly with the area of Bayesian inference, narrowing it down to issues related to the Machine learning, and often Pattern recognition and Directed graph. Adeel Razi has included themes like Electrophysiology, Algorithm, Visual motion and Premovement neuronal activity in his Bayesian probability study.

His most cited work include:

  • A DCM for resting state fMRI (258 citations)
  • A DCM for resting state fMRI (258 citations)
  • Bayesian model reduction and empirical Bayes for group (DCM) studies. (237 citations)

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

Adeel Razi mainly investigates Neuroscience, Dynamic causal modelling, Causal model, Resting state fMRI and Artificial intelligence. His Neuroscience course of study focuses on Huntington's disease and Neurodegeneration and Atrophy. His Dynamic causal modelling research includes elements of Divergence, Time series and Disinhibition.

His biological study spans a wide range of topics, including Econometrics, Bayesian probability, Vaccination, Pandemic and Brain mapping. His work deals with themes such as Algorithm, Cognitive neuroscience, Default mode network and Human Connectome Project, which intersect with Resting state fMRI. His work on Bayesian inference as part of general Artificial intelligence research is frequently linked to Graph, thereby connecting diverse disciplines of science.

He most often published in these fields:

  • Neuroscience (74.70%)
  • Dynamic causal modelling (57.23%)
  • Causal model (43.37%)

What were the highlights of his more recent work (between 2019-2021)?

  • Dynamic causal modelling (57.23%)
  • Causal model (43.37%)
  • Neuroscience (74.70%)

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

His primary areas of study are Dynamic causal modelling, Causal model, Neuroscience, Econometrics and Technical report. His Dynamic causal modelling study combines topics in areas such as Cortex, Positron emission tomography and Divergence. Adeel Razi has researched Divergence in several fields, including Computational neuroscience, Resting state fMRI, Cognitive neuroscience and Regression.

Adeel Razi combines subjects such as Marginal likelihood, Time series, Electroencephalography, Vaccination and Pandemic with his study of Causal model. His Resting fmri and Functional connectivity study in the realm of Neuroscience connects with subjects such as Rest. His Econometrics research focuses on Bayesian probability and how it relates to Convolutional neural network, Deep learning and Machine learning.

Between 2019 and 2021, his most popular works were:

  • Questions and controversies in the study of time-varying functional connectivity in resting fMRI (111 citations)
  • Questions and controversies in the study of time-varying functional connectivity in resting fMRI (111 citations)
  • Questions and controversies in the study of time-varying functional connectivity in resting fMRI (111 citations)

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

  • Statistics
  • Neuroscience
  • Artificial intelligence

Adeel Razi focuses on Causal model, Econometrics, Neuroscience, Bayesian probability and Dynamic causal modelling. His research integrates issues of Artificial intelligence, Electroencephalography and Pattern recognition in his study of Causal model. While the research belongs to areas of Econometrics, Adeel Razi spends his time largely on the problem of Pandemic, intersecting his research to questions surrounding Severe acute respiratory syndrome coronavirus 2.

His work on Functional connectivity and Resting fmri as part of general Neuroscience research is often related to Rest and Structure function, thus linking different fields of science. His Bayesian probability research incorporates themes from Test strategy and Time horizon. As a part of the same scientific family, Adeel Razi mostly works in the field of Dynamic causal modelling, focusing on Time series and, on occasion, Prior probability and Mismatch negativity.

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

A DCM for resting state fMRI

Karl J. Friston;Joshua Kahan;Bharat B. Biswal;Adeel Razi;Adeel Razi.
NeuroImage (2014)

315 Citations

Bayesian model reduction and empirical Bayes for group (DCM) studies.

Karl J. Friston;Vladimir Litvak;Ashwini Oswal;Adeel Razi;Adeel Razi.
NeuroImage (2016)

258 Citations

Construct validation of a DCM for resting state fMRI.

Adeel Razi;Adeel Razi;Joshua Kahan;Geraint Rees;Geraint Rees;Karl J. Friston.
NeuroImage (2015)

167 Citations

Secrecy Sum-Rates for Multi-User MIMO Regularized Channel Inversion Precoding

G. Geraci;M. Egan;Jinhong Yuan;A. Razi.
IEEE Transactions on Communications (2012)

164 Citations

Leveraging Data Science to Combat COVID-19: A Comprehensive Review

Siddique Latif;Muhammad Usman;Sanaullah Manzoor;Waleed Iqbal.
IEEE Transactions on Artificial Intelligence (2020)

142 Citations

Dynamic causal modelling revisited

Karl J. Friston;Katrin H. Preller;Katrin H. Preller;Christoph Mathys;Christoph Mathys;Hayriye Cagnan;Hayriye Cagnan.
NeuroImage (2017)

127 Citations

Questions and controversies in the study of time-varying functional connectivity in resting fMRI

Daniel J. Lurie;Daniel Kessler;Danielle S. Bassett;Richard F. Betzel.
Network Neuroscience , 4 (1) pp. 30-69. (2020) (2020)

111 Citations

Extrinsic and Intrinsic Brain Network Connectivity Maintains Cognition across the Lifespan Despite Accelerated Decay of Regional Brain Activation

Kamen A. Tsvetanov;Kamen A. Tsvetanov;Richard N.A. Henson;Lorraine K. Tyler;Adeel Razi.
The Journal of Neuroscience (2016)

108 Citations

Compensation in Preclinical Huntington's Disease: Evidence From the Track-On HD Study

Stefan Klöppel;Sarah Gregory;Elisa Scheller;Lora Minkova.
EBioMedicine (2015)

95 Citations

Large-scale DCMs for resting-state fMRI

Adeel Razi;Mohamed L. Seghier;Yuan Zhou;Yuan Zhou;Peter McColgan.
Network Neuroscience , 1 (3) pp. 222-241. (2017) (2017)

88 Citations

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