Quantitative language features identify placebo responders in chronic back pain-Reference-Cited by-同舟云学术

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Quantitative language features identify placebo responders in chronic back pain

Published:2021-01-05 Issue:6 Volume:162 Page:1692-1704
ISSN:0304-3959
Container-title:Pain
language:en
Short-container-title:PAIN

Author:

Berger Sara E.,Branco Paulo,Vachon-Presseau Etienne,Abdullah Taha B.,Cecchi Guillermo,Apkarian A. Vania

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Anesthesiology and Pain Medicine,Clinical Neurology,Neurology

Reference44 articles.

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2. A window into the intoxicated mind? Speech as an index of psychoactive drug effects;Bedi;Neuropsychopharmacol,2014

3. Automatic measurement of propositional idea density from part-of-speech tagging;Brown;Behav Res Methods,2008

4. O2.3. Automated analysis of recent-onset and prodromal schizophrenia;Cecchi;Schizophr Bull,2018

5. How to do things with (thousands of) words: computational approaches to discourse analysis in Alzheimer's disease;Clarke;Cortex,2020

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1. The Context Sets the Tone: A Literature Review on Emotion Recognition from Speech Using AI;Lecture Notes in Information Systems and Organisation;2024

2. Reattribution to Mind-Brain Processes and Recovery From Chronic Back Pain;JAMA Network Open;2023-09-28

3. The Impact of COVID-19 on Chronic Pain: Multidimensional Clustering Reveals Deep Insights into Spinal Cord Stimulation Patients;2023 IEEE International Conference on Digital Health (ICDH);2023-07

4. Chronic Pain Patient Narratives Allow for the Estimation of Current Pain Intensity;2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS);2023-06

5. Chronic pain patient narratives allow for the estimation of current pain intensity;2023-01-12

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