Objectives: This study aims to systematically review the literature on the
computational processing of the language of pain, whether generated by patients
or physicians, identifying current trends and challenges. Methods: Following
the PRISMA guidelines, a comprehensive literature search was conducted to
select relevant studies on the computational processing of the language of pain
and answer pre-defined research questions. Data extraction and synthesis were
performed to categorize selected studies according to their primary purpose and
outcome, patient and pain population, textual data, computational methodology,
and outcome targets. Results: Physician-generated language of pain,
specifically from clinical notes, was the most used data. Tasks included
patient diagnosis and triaging, identification of pain mentions, treatment
response prediction, biomedical entity extraction, correlation of linguistic
features with clinical states, and lexico-semantic analysis of pain narratives.
Only one study included previous linguistic knowledge on pain utterances in
their experimental setup. Most studies targeted their outcomes for physicians,
either directly as clinical tools or as indirect knowledge. The least targeted
stage of clinical pain care was self-management, in which patients are most
involved. The least studied dimensions of pain were affective and
sociocultural. Only two studies measured how physician performance on clinical
tasks improved with the inclusion of the proposed algorithm. Discussion: This
study found that future research should focus on analyzing patient-generated
language of pain, developing patient-centered resources for self-management and
patient-empowerment, exploring affective and sociocultural aspects of pain, and
measuring improvements in physician performance when aided by the proposed
tools.

该研究旨在系统综述有关疼痛语言的计算处理的文献，无论是由患者还是医生产生，以确定当前的趋势和挑战。