Literature DB >> 29112192

The perilous path from publication to practice.

A M Chekroud1,2, N Koutsouleris3.   

Abstract

Mesh：

Year:  2017        PMID： 29112192     DOI： 10.1038/mp.2017.227

Source DB:  PubMed          Journal:  Mol Psychiatry        ISSN： 1359-4184            Impact factor:   15.992


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  15 in total

1.  Why Psychiatry Needs Data Science and Data Science Needs Psychiatry: Connecting With Technology.

Authors:  John Torous; Justin T Baker
Journal:  JAMA Psychiatry       Date:  2016-01       Impact factor: 21.596

2.  Big data. The parable of Google Flu: traps in big data analysis.

Authors:  David Lazer; Ryan Kennedy; Gary King; Alessandro Vespignani
Journal:  Science       Date:  2014-03-14       Impact factor: 47.728

3.  Evidence-Based Pragmatic Psychiatry-A Call to Action.

Authors:  Martin P Paulus
Journal:  JAMA Psychiatry       Date:  2017-12-01       Impact factor: 21.596

Review 4.  Personalized medicine for depression: can we match patients with treatments?

Authors:  Gregory E Simon; Roy H Perlis
Journal:  Am J Psychiatry       Date:  2010-09-15       Impact factor: 18.112

5.  Telephone screening, outreach, and care management for depressed workers and impact on clinical and work productivity outcomes: a randomized controlled trial.

Authors:  Philip S Wang; Gregory E Simon; Jerry Avorn; Francisca Azocar; Evette J Ludman; Joyce McCulloch; Maria Z Petukhova; Ronald C Kessler
Journal:  JAMA       Date:  2007-09-26       Impact factor: 56.272

6.  Cross-trial prediction of treatment outcome in depression: a machine learning approach.

Authors:  Adam Mourad Chekroud; Ryan Joseph Zotti; Zarrar Shehzad; Ralitza Gueorguieva; Marcia K Johnson; Madhukar H Trivedi; Tyrone D Cannon; John Harrison Krystal; Philip Robert Corlett
Journal:  Lancet Psychiatry       Date:  2016-01-21       Impact factor: 27.083

7.  Detecting influenza epidemics using search engine query data.

Authors:  Jeremy Ginsberg; Matthew H Mohebbi; Rajan S Patel; Lynnette Brammer; Mark S Smolinski; Larry Brilliant
Journal:  Nature       Date:  2009-02-19       Impact factor: 49.962

8.  Default network connectivity reflects the level of consciousness in non-communicative brain-damaged patients.

Authors:  Audrey Vanhaudenhuyse; Quentin Noirhomme; Luaba J-F Tshibanda; Marie-Aurelie Bruno; Pierre Boveroux; Caroline Schnakers; Andrea Soddu; Vincent Perlbarg; Didier Ledoux; Jean-François Brichant; Gustave Moonen; Pierre Maquet; Michael D Greicius; Steven Laureys; Melanie Boly
Journal:  Brain       Date:  2009-12-23       Impact factor: 13.501

9.  Reevaluating the Efficacy and Predictability of Antidepressant Treatments: A Symptom Clustering Approach.

Authors:  Adam M Chekroud; Ralitza Gueorguieva; Harlan M Krumholz; Madhukar H Trivedi; John H Krystal; Gregory McCarthy
Journal:  JAMA Psychiatry       Date:  2017-04-01       Impact factor: 21.596

10.  Detecting Neuroimaging Biomarkers for Psychiatric Disorders: Sample Size Matters.

Authors:  Hugo G Schnack; René S Kahn
Journal:  Front Psychiatry       Date:  2016-03-31       Impact factor: 4.157
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  7 in total

1.  Prediction Models of Functional Outcomes for Individuals in the Clinical High-Risk State for Psychosis or With Recent-Onset Depression: A Multimodal, Multisite Machine Learning Analysis.

Authors:  Nikolaos Koutsouleris; Lana Kambeitz-Ilankovic; Stephan Ruhrmann; Marlene Rosen; Anne Ruef; Dominic B Dwyer; Marco Paolini; Katharine Chisholm; Joseph Kambeitz; Theresa Haidl; André Schmidt; John Gillam; Frauke Schultze-Lutter; Peter Falkai; Maximilian Reiser; Anita Riecher-Rössler; Rachel Upthegrove; Jarmo Hietala; Raimo K R Salokangas; Christos Pantelis; Eva Meisenzahl; Stephen J Wood; Dirk Beque; Paolo Brambilla; Stefan Borgwardt
Journal:  JAMA Psychiatry       Date:  2018-11-01       Impact factor: 21.596

2.  Development and Validation of a Dynamic Risk Prediction Model to Forecast Psychosis Onset in Patients at Clinical High Risk.

Authors:  Erich Studerus; Katharina Beck; Paolo Fusar-Poli; Anita Riecher-Rössler
Journal:  Schizophr Bull       Date:  2020-02-26       Impact factor: 9.306

Review 3.  Prediction complements explanation in understanding the developing brain.

Authors:  Monica D Rosenberg; B J Casey; Avram J Holmes
Journal:  Nat Commun       Date:  2018-02-21       Impact factor: 14.919

4.  Latent variable mixture modelling and individual treatment prediction.

Authors:  Rob Saunders; Joshua E J Buckman; Stephen Pilling
Journal:  Behav Res Ther       Date:  2019-10-28

5.  Real-world implementation of precision psychiatry: Transdiagnostic risk calculator for the automatic detection of individuals at-risk of psychosis.

Authors:  Dominic Oliver; Giulia Spada; Craig Colling; Matthew Broadbent; Helen Baldwin; Rashmi Patel; Robert Stewart; Daniel Stahl; Richard Dobson; Philip McGuire; Paolo Fusar-Poli
Journal:  Schizophr Res       Date:  2020-06-19       Impact factor: 4.939

6.  How machine-learning recommendations influence clinician treatment selections: the example of the antidepressant selection.

Authors:  Maia Jacobs; Melanie F Pradier; Thomas H McCoy; Roy H Perlis; Finale Doshi-Velez; Krzysztof Z Gajos
Journal:  Transl Psychiatry       Date:  2021-02-04       Impact factor: 6.222

7.  Implementing Precision Psychiatry: A Systematic Review of Individualized Prediction Models for Clinical Practice.

Authors:  Gonzalo Salazar de Pablo; Erich Studerus; Julio Vaquerizo-Serrano; Jessica Irving; Ana Catalan; Dominic Oliver; Helen Baldwin; Andrea Danese; Seena Fazel; Ewout W Steyerberg; Daniel Stahl; Paolo Fusar-Poli
Journal:  Schizophr Bull       Date:  2021-03-16       Impact factor: 9.306
  7 in total

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