Evidence map›Paper›PMID 39211548›Full record

ReviewiScience2024

Pain recognition and pain empathy from a human-centered AI perspective.

Siqi Cao, Di Fu, Xu Yang, Stefan Wermter, Xun Liu, Haiyan Wu

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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

6 authors.

Siqi CaoCAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.
Di FuSchool of Psychology, University of Surrey, Guildford, UK.
Xu YangState Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Stefan WermterDepartment of Informatics, University of Hamburg, Hamburg, Germany.
Xun LiuCAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.
Haiyan WuCentre for Cognitive and Brain Sciences and Department of Psychology, University of Macau, Taipa, Macau.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sensory and emotional experiences are essential for mental and physical well-being, especially within the realm of psychiatry. This article highlights recent advances in cognitive neuroscience, emphasizing the significance of pain recognition and empathic artificial intelligence (AI) in healthcare. We provide an overview of the recent development process in computational pain recognition and cognitive neuroscience regarding the mechanisms of pain and empathy. Through a comprehensive discussion, the article delves into critical questions such as the methodologies for AI in recognizing pain from diverse sources of information, the necessity for AI to exhibit empathic responses, and the associated advantages and obstacles linked with the development of empathic AI. Moreover, insights into the prospects and challenges are emphasized in relation to fostering artificial empathy. By delineating potential pathways for future research, the article aims to contribute to developing effective assistants equipped with empathic capabilities, thereby introducing safe and meaningful interactions between humans and AI, particularly in the context of mental health and psychiatry.

Indexed as

Applied sciencesCognitive neuroscienceSocial sciences

Identifiers

PMID39211548
PMCPMC11357883

What OpenQuestion holds

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LicenceCC BY-NC
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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.