A citation-based method for searching scientific literature

Graziella Orrù, William Pettersson-Yeo, Andre F Marquand, Giuseppe Sartori, Andrea Mechelli. Neurosci Biobehav Rev 2012
Times Cited: 473







List of co-cited articles
734 articles co-cited >1



Times Cited
  Times     Co-cited
Similarity


Building better biomarkers: brain models in translational neuroimaging.
Choong-Wan Woo, Luke J Chang, Martin A Lindquist, Tor D Wager. Nat Neurosci 2017
327
19

Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls.
Mohammad R Arbabshirani, Sergey Plis, Jing Sui, Vince D Calhoun. Neuroimage 2017
300
18

From estimating activation locality to predicting disorder: A review of pattern recognition for neuroimaging-based psychiatric diagnostics.
Thomas Wolfers, Jan K Buitelaar, Christian F Beckmann, Barbara Franke, Andre F Marquand. Neurosci Biobehav Rev 2015
138
17


Machine learning classifiers and fMRI: a tutorial overview.
Francisco Pereira, Tom Mitchell, Matthew Botvinick. Neuroimage 2009
829
12

Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain.
N Tzourio-Mazoyer, B Landeau, D Papathanassiou, F Crivello, O Etard, N Delcroix, B Mazoyer, M Joliot. Neuroimage 2002
11


Deep learning.
Yann LeCun, Yoshua Bengio, Geoffrey Hinton. Nature 2015
11

Automatic classification of MR scans in Alzheimer's disease.
Stefan Klöppel, Cynthia M Stonnington, Carlton Chu, Bogdan Draganski, Rachael I Scahill, Jonathan D Rohrer, Nick C Fox, Clifford R Jack, John Ashburner, Richard S J Frackowiak. Brain 2008
553
10

Can structural MRI aid in clinical classification? A machine learning study in two independent samples of patients with schizophrenia, bipolar disorder and healthy subjects.
Hugo G Schnack, Mireille Nieuwenhuis, Neeltje E M van Haren, Lucija Abramovic, Thomas W Scheewe, Rachel M Brouwer, Hilleke E Hulshoff Pol, René S Kahn. Neuroimage 2014
110
9

Detecting neuroimaging biomarkers for schizophrenia: a meta-analysis of multivariate pattern recognition studies.
Joseph Kambeitz, Lana Kambeitz-Ilankovic, Stefan Leucht, Stephen Wood, Christos Davatzikos, Berend Malchow, Peter Falkai, Nikolaos Koutsouleris. Neuropsychopharmacology 2015
101
9

Deep learning for neuroimaging: a validation study.
Sergey M Plis, Devon R Hjelm, Ruslan Salakhutdinov, Elena A Allen, Henry J Bockholt, Jeffrey D Long, Hans J Johnson, Jane S Paulsen, Jessica A Turner, Vince D Calhoun. Front Neurosci 2014
163
8


Classification of schizophrenia patients and healthy controls from structural MRI scans in two large independent samples.
Mireille Nieuwenhuis, Neeltje E M van Haren, Hilleke E Hulshoff Pol, Wiepke Cahn, René S Kahn, Hugo G Schnack. Neuroimage 2012
101
8

Resting-state connectivity biomarkers define neurophysiological subtypes of depression.
Andrew T Drysdale, Logan Grosenick, Jonathan Downar, Katharine Dunlop, Farrokh Mansouri, Yue Meng, Robert N Fetcho, Benjamin Zebley, Desmond J Oathes, Amit Etkin,[...]. Nat Med 2017
745
8

Machine Learning Approaches for Clinical Psychology and Psychiatry.
Dominic B Dwyer, Peter Falkai, Nikolaos Koutsouleris. Annu Rev Clin Psychol 2018
164
8

Use of neuroanatomical pattern classification to identify subjects in at-risk mental states of psychosis and predict disease transition.
Nikolaos Koutsouleris, Eva M Meisenzahl, Christos Davatzikos, Ronald Bottlender, Thomas Frodl, Johanna Scheuerecker, Gisela Schmitt, Thomas Zetzsche, Petra Decker, Maximilian Reiser,[...]. Arch Gen Psychiatry 2009
271
7

Using genetic, cognitive and multi-modal neuroimaging data to identify ultra-high-risk and first-episode psychosis at the individual level.
W Pettersson-Yeo, S Benetti, A F Marquand, F Dell'acqua, S C R Williams, P Allen, D Prata, P McGuire, A Mechelli. Psychol Med 2013
76
9

Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion.
Jonathan D Power, Kelly A Barnes, Abraham Z Snyder, Bradley L Schlaggar, Steven E Petersen. Neuroimage 2012
7

Machine Learning for Precision Psychiatry: Opportunities and Challenges.
Danilo Bzdok, Andreas Meyer-Lindenberg. Biol Psychiatry Cogn Neurosci Neuroimaging 2018
163
7


Identification of Distinct Psychosis Biotypes Using Brain-Based Biomarkers.
Brett A Clementz, John A Sweeney, Jordan P Hamm, Elena I Ivleva, Lauren E Ethridge, Godfrey D Pearlson, Matcheri S Keshavan, Carol A Tamminga. Am J Psychiatry 2016
326
6

The positive and negative syndrome scale (PANSS) for schizophrenia.
S R Kay, A Fiszbein, L A Opler. Schizophr Bull 1987
6

Pattern of neural responses to verbal fluency shows diagnostic specificity for schizophrenia and bipolar disorder.
Sergi G Costafreda, Cynthia H Y Fu, Marco Picchioni, Timothea Toulopoulou, Colm McDonald, Eugenia Kravariti, Muriel Walshe, Diana Prata, Robin M Murray, Philip K McGuire. BMC Psychiatry 2011
124
6

FreeSurfer.
Bruce Fischl. Neuroimage 2012
6

Evaluation of machine learning algorithms and structural features for optimal MRI-based diagnostic prediction in psychosis.
Raymond Salvador, Joaquim Radua, Erick J Canales-Rodríguez, Aleix Solanes, Salvador Sarró, José M Goikolea, Alicia Valiente, Gemma C Monté, María Del Carmen Natividad, Amalia Guerrero-Pedraza,[...]. PLoS One 2017
39
15


A review of feature reduction techniques in neuroimaging.
Benson Mwangi, Tian Siva Tian, Jair C Soares. Neuroinformatics 2014
171
6

Individualized differential diagnosis of schizophrenia and mood disorders using neuroanatomical biomarkers.
Nikolaos Koutsouleris, Eva M Meisenzahl, Stefan Borgwardt, Anita Riecher-Rössler, Thomas Frodl, Joseph Kambeitz, Yanis Köhler, Peter Falkai, Hans-Jürgen Möller, Maximilian Reiser,[...]. Brain 2015
82
7

A neuromarker of sustained attention from whole-brain functional connectivity.
Monica D Rosenberg, Emily S Finn, Dustin Scheinost, Xenophon Papademetris, Xilin Shen, R Todd Constable, Marvin M Chun. Nat Neurosci 2016
338
6

Ten simple rules for predictive modeling of individual differences in neuroimaging.
Dustin Scheinost, Stephanie Noble, Corey Horien, Abigail S Greene, Evelyn Mr Lake, Mehraveh Salehi, Siyuan Gao, Xilin Shen, David O'Connor, Daniel S Barron,[...]. Neuroimage 2019
76
7




Deep learning in neural networks: an overview.
Jürgen Schmidhuber. Neural Netw 2015
6


Assessing and tuning brain decoders: Cross-validation, caveats, and guidelines.
Gaël Varoquaux, Pradeep Reddy Raamana, Denis A Engemann, Andrés Hoyos-Idrobo, Yannick Schwartz, Bertrand Thirion. Neuroimage 2017
215
6

Disease prediction in the at-risk mental state for psychosis using neuroanatomical biomarkers: results from the FePsy study.
Nikolaos Koutsouleris, Stefan Borgwardt, Eva M Meisenzahl, Ronald Bottlender, Hans-Jürgen Möller, Anita Riecher-Rössler. Schizophr Bull 2012
99
5

Distinguishing prodromal from first-episode psychosis using neuroanatomical single-subject pattern recognition.
Stefan Borgwardt, Nikolaos Koutsouleris, Jacqueline Aston, Erich Studerus, Renata Smieskova, Anita Riecher-Rössler, Eva M Meisenzahl. Schizophr Bull 2013
47
10

Research domain criteria (RDoC): toward a new classification framework for research on mental disorders.
Thomas Insel, Bruce Cuthbert, Marjorie Garvey, Robert Heinssen, Daniel S Pine, Kevin Quinn, Charles Sanislow, Philip Wang. Am J Psychiatry 2010
5

Representation learning: a review and new perspectives.
Yoshua Bengio, Aaron Courville, Pascal Vincent. IEEE Trans Pattern Anal Mach Intell 2013
820
5

A Hybrid Machine Learning Method for Fusing fMRI and Genetic Data: Combining both Improves Classification of Schizophrenia.
Honghui Yang, Jingyu Liu, Jing Sui, Godfrey Pearlson, Vince D Calhoun. Front Hum Neurosci 2010
96
5


Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness.
Vince D Calhoun, Jing Sui. Biol Psychiatry Cogn Neurosci Neuroimaging 2016
127
5

An empirical comparison of different approaches for combining multimodal neuroimaging data with support vector machine.
William Pettersson-Yeo, Stefania Benetti, Andre F Marquand, Richard Joules, Marco Catani, Steve C R Williams, Paul Allen, Philip McGuire, Andrea Mechelli. Front Neurosci 2014
19
26

Classifying Schizophrenia Using Multimodal Multivariate Pattern Recognition Analysis: Evaluating the Impact of Individual Clinical Profiles on the Neurodiagnostic Performance.
Carlos Cabral, Lana Kambeitz-Ilankovic, Joseph Kambeitz, Vince D Calhoun, Dominic B Dwyer, Sebastian von Saldern, Maria F Urquijo, Peter Falkai, Nikolaos Koutsouleris. Schizophr Bull 2016
40
12

Prediction of individual brain maturity using fMRI.
Nico U F Dosenbach, Binyam Nardos, Alexander L Cohen, Damien A Fair, Jonathan D Power, Jessica A Church, Steven M Nelson, Gagan S Wig, Alecia C Vogel, Christina N Lessov-Schlaggar,[...]. Science 2010
5

Diagnostic neuroimaging across diseases.
Stefan Klöppel, Ahmed Abdulkadir, Clifford R Jack, Nikolaos Koutsouleris, Janaina Mourão-Miranda, Prashanthi Vemuri. Neuroimage 2012
167
5

Brain morphometric biomarkers distinguishing unipolar and bipolar depression. A voxel-based morphometry-pattern classification approach.
Ronny Redlich, Jorge J R Almeida, Dominik Grotegerd, Nils Opel, Harald Kugel, Walter Heindel, Volker Arolt, Mary L Phillips, Udo Dannlowski. JAMA Psychiatry 2014
162
5

Whole-brain morphometric study of schizophrenia revealing a spatially complex set of focal abnormalities.
Christos Davatzikos, Dinggang Shen, Ruben C Gur, Xiaoying Wu, Dengfeng Liu, Yong Fan, Paul Hughett, Bruce I Turetsky, Raquel E Gur. Arch Gen Psychiatry 2005
196
5


Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.