Salah N El-Tallawy, Joseph V Pergolizzi, Ingrid Vasiliu-Feltes, Rania S Ahmed, JoAnn K LeQuang, Hamdy N El-Tallawy, Giustino Varrassi, Mohamed S Nagiub
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By examining the existing literature, research gaps, and future directions, this article aims to guide further advancements in the field of pain management. An online database search was conducted via multiple websites to identify the relevant articles. The inclusion criteria were English articles published between January 2014 and January 2024). Articles that were available as full text clinical trials, observational studies, review articles, systemic reviews, and meta-analyses were included in this review. The exclusion criteria were articles that were not in the English language, not available as free full text, those involving pediatric patients, case reports, and editorials. A total of (47) articles were included in this review. In conclusion, the application of AI in pain management could present promising solutions for pain assessment. AI can potentially increase the accuracy, precision, and efficiency of objective pain assessment.</p>","PeriodicalId":19908,"journal":{"name":"Pain and Therapy","volume":" ","pages":"293-317"},"PeriodicalIF":4.1000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11111436/pdf/","citationCount":"0","resultStr":"{\"title\":\"Incorporation of \\\"Artificial Intelligence\\\" for Objective Pain Assessment: A Comprehensive Review.\",\"authors\":\"Salah N El-Tallawy, Joseph V Pergolizzi, Ingrid Vasiliu-Feltes, Rania S Ahmed, JoAnn K LeQuang, Hamdy N El-Tallawy, Giustino Varrassi, Mohamed S Nagiub\",\"doi\":\"10.1007/s40122-024-00584-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Pain is a significant health issue, and pain assessment is essential for proper diagnosis, follow-up, and effective management of pain. The conventional methods of pain assessment often suffer from subjectivity and variability. The main issue is to understand better how people experience pain. In recent years, artificial intelligence (AI) has been playing a growing role in improving clinical diagnosis and decision-making. The application of AI offers promising opportunities to improve the accuracy and efficiency of pain assessment. This review article provides an overview of the current state of AI in pain assessment and explores its potential for improving accuracy, efficiency, and personalized care. By examining the existing literature, research gaps, and future directions, this article aims to guide further advancements in the field of pain management. An online database search was conducted via multiple websites to identify the relevant articles. The inclusion criteria were English articles published between January 2014 and January 2024). Articles that were available as full text clinical trials, observational studies, review articles, systemic reviews, and meta-analyses were included in this review. The exclusion criteria were articles that were not in the English language, not available as free full text, those involving pediatric patients, case reports, and editorials. A total of (47) articles were included in this review. In conclusion, the application of AI in pain management could present promising solutions for pain assessment. AI can potentially increase the accuracy, precision, and efficiency of objective pain assessment.</p>\",\"PeriodicalId\":19908,\"journal\":{\"name\":\"Pain and Therapy\",\"volume\":\" \",\"pages\":\"293-317\"},\"PeriodicalIF\":4.1000,\"publicationDate\":\"2024-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11111436/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Pain and Therapy\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s40122-024-00584-8\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/3/2 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pain and Therapy","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s40122-024-00584-8","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/3/2 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Incorporation of "Artificial Intelligence" for Objective Pain Assessment: A Comprehensive Review.
Pain is a significant health issue, and pain assessment is essential for proper diagnosis, follow-up, and effective management of pain. The conventional methods of pain assessment often suffer from subjectivity and variability. The main issue is to understand better how people experience pain. In recent years, artificial intelligence (AI) has been playing a growing role in improving clinical diagnosis and decision-making. The application of AI offers promising opportunities to improve the accuracy and efficiency of pain assessment. This review article provides an overview of the current state of AI in pain assessment and explores its potential for improving accuracy, efficiency, and personalized care. By examining the existing literature, research gaps, and future directions, this article aims to guide further advancements in the field of pain management. An online database search was conducted via multiple websites to identify the relevant articles. The inclusion criteria were English articles published between January 2014 and January 2024). Articles that were available as full text clinical trials, observational studies, review articles, systemic reviews, and meta-analyses were included in this review. The exclusion criteria were articles that were not in the English language, not available as free full text, those involving pediatric patients, case reports, and editorials. A total of (47) articles were included in this review. In conclusion, the application of AI in pain management could present promising solutions for pain assessment. AI can potentially increase the accuracy, precision, and efficiency of objective pain assessment.
期刊介绍：
Pain and Therapy is an international, open access, peer-reviewed, rapid publication journal dedicated to the publication of high-quality clinical (all phases), observational, real-world, and health outcomes research around the discovery, development, and use of pain therapies and pain-related devices. Studies relating to diagnosis, pharmacoeconomics, public health, quality of life, and patient care, management, and education are also encouraged.
Areas of focus include, but are not limited to, acute pain, cancer pain, chronic pain, headache and migraine, neuropathic pain, opioids, palliative care and pain ethics, peri- and post-operative pain as well as rheumatic pain and fibromyalgia.
The journal is of interest to a broad audience of pharmaceutical and healthcare professionals and publishes original research, reviews, case reports, trial protocols, short communications such as commentaries and editorials, and letters. The journal is read by a global audience and receives submissions from around the world. Pain and Therapy will consider all scientifically sound research be it positive, confirmatory or negative data. Submissions are welcomed whether they relate to an international and/or a country-specific audience, something that is crucially important when researchers are trying to target more specific patient populations. This inclusive approach allows the journal to assist in the dissemination of all scientifically and ethically sound research.
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