Evidence map›Paper›PMID 36687372›Full record

ReviewWorld journal of psychiatry2023

Emotion recognition support system: Where physicians and psychiatrists meet linguists and data engineers.

Peyman Adibi, Simindokht Kalani, Sayed Jalal Zahabi, Homa Asadi, Mohsen Bakhtiar, Mohammad Reza Heidarpour, Hamidreza Roohafza, Hassan Shahoon, Mohammad Amouzadeh

Open access · diamondAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in World journal of psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
2.3field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 7 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 1 country.

Peyman AdibiIsfahan Gastroenterology and Hepatology Research Center, Isfahan University of Medical Sciences, Isfahan 8174673461, Iran.
Simindokht KalaniDepartment of Psychology, University of Isfahan, Isfahan 8174673441, Iran.
Sayed Jalal ZahabiDepartment of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan 8415683111, Iran. zahabi@iut.ac.ir.
Homa AsadiDepartment of Linguistics, University of Isfahan, Isfahan 8174673441, Iran.
Mohsen BakhtiarDepartment of Linguistics, Ferdowsi University of Mashhad, Mashhad 9177948974, Iran.
Mohammad Reza HeidarpourDepartment of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan 8415683111, Iran.
Hamidreza RoohafzaDepartment of Psychocardiology, Cardiac Rehabilitation Research Center, Cardiovascular Research Institute (WHO-Collaborating Center), Isfahan University of Medical Sciences, Isfahan 8187698191, Iran.
Hassan ShahoonIsfahan Gastroenterology and Hepatology Research Center, Isfahan University of Medical Sciences, Isfahan 8174673461, Iran.
Mohammad AmouzadehDepartment of Linguistics, University of Isfahan, Isfahan 8174673441, Iran.
Isfahan University of Medical Sciences · IRIsfahan University of Technology · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An important factor in the course of daily medical diagnosis and treatment is understanding patients' emotional states by the caregiver physicians. However, patients usually avoid speaking out their emotions when expressing their somatic symptoms and complaints to their non-psychiatrist doctor. On the other hand, clinicians usually lack the required expertise (or time) and have a deficit in mining various verbal and non-verbal emotional signals of the patients. As a result, in many cases, there is an emotion recognition barrier between the clinician and the patients making all patients seem the same except for their different somatic symptoms. In particular, we aim to identify and combine three major disciplines (psychology, linguistics, and data science) approaches for detecting emotions from verbal communication and propose an integrated solution for emotion recognition support. Such a platform may give emotional guides and indices to the clinician based on verbal communication at the consultation time.

Indexed as

Data scienceEmotionsLinguisticsPhysician-Patient relationsPsychologyVerbal behavior

Identifiers

PMID36687372
PMCPMC9850871
OpenAlexW4315784924

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.