人工智能在治疗慢性背痛中的应用。

IF 3.4 3区 医学 Q2 CLINICAL NEUROLOGY Korean Journal of Pain Pub Date : 2023-10-01 DOI:10.3344/kjp.23239
Kenny Do, Eric Kawana, Benjamin Vachirakorntong, Jenifer Do, Ross Seibel
{"title":"人工智能在治疗慢性背痛中的应用。","authors":"Kenny Do, Eric Kawana, Benjamin Vachirakorntong, Jenifer Do, Ross Seibel","doi":"10.3344/kjp.23239","DOIUrl":null,"url":null,"abstract":"Chronic back pain is a debilitating disorder that is believed to be experienced by close to a quarter of the adult population globally [1]. With the recent advancements in technology, artificial intelligence (AI) has played a crucial role in healthcare, such as safely filtering patient information, analyzing medical imaging, providing recommendations for diagnoses, and even acting as virtual assistants for both physicians and patients [2]. One of the ways AI has been used in pain medicine and in helping patients with low back pain is aiding in the diagnoses of various conditions through interpretations of MRI, CT, X-ray, and other imaging modalities. Previous studies have already assessed the accuracy of artificial intelligence in diagnosing low back pain associated with spinal stenosis, disc degeneration, and lumbar arthritis [3]. One systematic review found that through the use of various machine learning models, physicians can use AI to differentiate patients with and without low back pain through the analysis of brain MRI [3]. AI can be used to filter and interpret clinical data, electromyography studies, and even physical motion to diagnose or predict the onset of various low back pain conditions. Some studies in the systematic review reported an accuracy of up to over 90% [3]. AI can be used to not only interpret these imaging modalities, but it can be used to enhance and even reconstruct an entire imaging of the spine as well. AI algorithms can be trained to differentiate between noisy and clear MRI or CT images, where this training can be applied by having the software reconstruct high-quality images [4]. This will allow the radiologists, interventional pain physicians, and even spine surgeons to have a better understanding of the disease at hand and how to best operate on patients. Past studies have even mentioned the use of AI to create completely new images from given data. For example, with a given MRI image, AI can be used to translate the information into a synthetic CT image, allowing physicians to obtain a more comprehensive view of a patient’s spine or nerves [4]. Even something as mundane as labeling the different parts can be completed by AI to save the physician's time. AI can also be effectively used to identify pain using neurophysiology-based methods [5]. Electroencephalography (EEG), a technique that records the brain’s electrical impulses, has been used to identify and even measure pain intensity [5,6]. A systematic review examined 22","PeriodicalId":56252,"journal":{"name":"Korean Journal of Pain","volume":"36 4","pages":"478-480"},"PeriodicalIF":3.4000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/ca/e5/kjp-36-4-478.PMC10551394.pdf","citationCount":"0","resultStr":"{\"title\":\"The use of artificial intelligence in treating chronic back pain.\",\"authors\":\"Kenny Do, Eric Kawana, Benjamin Vachirakorntong, Jenifer Do, Ross Seibel\",\"doi\":\"10.3344/kjp.23239\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Chronic back pain is a debilitating disorder that is believed to be experienced by close to a quarter of the adult population globally [1]. With the recent advancements in technology, artificial intelligence (AI) has played a crucial role in healthcare, such as safely filtering patient information, analyzing medical imaging, providing recommendations for diagnoses, and even acting as virtual assistants for both physicians and patients [2]. One of the ways AI has been used in pain medicine and in helping patients with low back pain is aiding in the diagnoses of various conditions through interpretations of MRI, CT, X-ray, and other imaging modalities. Previous studies have already assessed the accuracy of artificial intelligence in diagnosing low back pain associated with spinal stenosis, disc degeneration, and lumbar arthritis [3]. One systematic review found that through the use of various machine learning models, physicians can use AI to differentiate patients with and without low back pain through the analysis of brain MRI [3]. AI can be used to filter and interpret clinical data, electromyography studies, and even physical motion to diagnose or predict the onset of various low back pain conditions. Some studies in the systematic review reported an accuracy of up to over 90% [3]. AI can be used to not only interpret these imaging modalities, but it can be used to enhance and even reconstruct an entire imaging of the spine as well. AI algorithms can be trained to differentiate between noisy and clear MRI or CT images, where this training can be applied by having the software reconstruct high-quality images [4]. This will allow the radiologists, interventional pain physicians, and even spine surgeons to have a better understanding of the disease at hand and how to best operate on patients. Past studies have even mentioned the use of AI to create completely new images from given data. For example, with a given MRI image, AI can be used to translate the information into a synthetic CT image, allowing physicians to obtain a more comprehensive view of a patient’s spine or nerves [4]. Even something as mundane as labeling the different parts can be completed by AI to save the physician's time. AI can also be effectively used to identify pain using neurophysiology-based methods [5]. Electroencephalography (EEG), a technique that records the brain’s electrical impulses, has been used to identify and even measure pain intensity [5,6]. A systematic review examined 22\",\"PeriodicalId\":56252,\"journal\":{\"name\":\"Korean Journal of Pain\",\"volume\":\"36 4\",\"pages\":\"478-480\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2023-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/ca/e5/kjp-36-4-478.PMC10551394.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Korean Journal of Pain\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3344/kjp.23239\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Korean Journal of Pain","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3344/kjp.23239","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
The use of artificial intelligence in treating chronic back pain.
Chronic back pain is a debilitating disorder that is believed to be experienced by close to a quarter of the adult population globally [1]. With the recent advancements in technology, artificial intelligence (AI) has played a crucial role in healthcare, such as safely filtering patient information, analyzing medical imaging, providing recommendations for diagnoses, and even acting as virtual assistants for both physicians and patients [2]. One of the ways AI has been used in pain medicine and in helping patients with low back pain is aiding in the diagnoses of various conditions through interpretations of MRI, CT, X-ray, and other imaging modalities. Previous studies have already assessed the accuracy of artificial intelligence in diagnosing low back pain associated with spinal stenosis, disc degeneration, and lumbar arthritis [3]. One systematic review found that through the use of various machine learning models, physicians can use AI to differentiate patients with and without low back pain through the analysis of brain MRI [3]. AI can be used to filter and interpret clinical data, electromyography studies, and even physical motion to diagnose or predict the onset of various low back pain conditions. Some studies in the systematic review reported an accuracy of up to over 90% [3]. AI can be used to not only interpret these imaging modalities, but it can be used to enhance and even reconstruct an entire imaging of the spine as well. AI algorithms can be trained to differentiate between noisy and clear MRI or CT images, where this training can be applied by having the software reconstruct high-quality images [4]. This will allow the radiologists, interventional pain physicians, and even spine surgeons to have a better understanding of the disease at hand and how to best operate on patients. Past studies have even mentioned the use of AI to create completely new images from given data. For example, with a given MRI image, AI can be used to translate the information into a synthetic CT image, allowing physicians to obtain a more comprehensive view of a patient’s spine or nerves [4]. Even something as mundane as labeling the different parts can be completed by AI to save the physician's time. AI can also be effectively used to identify pain using neurophysiology-based methods [5]. Electroencephalography (EEG), a technique that records the brain’s electrical impulses, has been used to identify and even measure pain intensity [5,6]. A systematic review examined 22
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Korean Journal of Pain
Korean Journal of Pain Medicine-Anesthesiology and Pain Medicine
CiteScore
5.40
自引率
7.10%
发文量
57
审稿时长
16 weeks
期刊介绍: Korean Journal of Pain (Korean J Pain, KJP) is the official journal of the Korean Pain Society, founded in 1986. It has been published since 1988. It publishes peer reviewed original articles related to all aspects of pain, including clinical and basic research, patient care, education, and health policy. It has been published quarterly in English since 2009 (on the first day of January, April, July, and October). In addition, it has also become the official journal of the International Spinal Pain Society since 2016. The mission of the Journal is to improve the care of patients in pain by providing a forum for clinical researchers, basic scientists, clinicians, and other health professionals. The circulation number per issue is 50.
期刊最新文献
Ultrasound-guided pain management: pros, cons, and benefits for the Philippines. Retraction: Comparison of the efficacy of genicular nerve phenol neurolysis and radiofrequency ablation for pain management in patients with knee osteoarthritis. A critical factor in resistant piriformis syndrome cases: awareness of sacrotuberous ligament pain. Effect of ultrasound-guided ilioinguinal-iliohypogastric nerve block on chronic pain in patients undergoing open inguinal hernia surgery under spinal anesthesia: a randomized double-blind study. Ultrasound-guided transoral pterygopalatine fossa block: cadaveric elaboration of a novel technique.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1