{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T21:05:23Z","timestamp":1785359123730,"version":"3.55.0"},"reference-count":24,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"content-domain":{"domain":["neuromodulationjournal.org","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neuromodulation: Technology at the Neural Interface"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1016\/j.neurom.2026.06.464","type":"journal-article","created":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T23:36:41Z","timestamp":1782257801000},"update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["Proof of Concept of Natural Language Processing in Predicting Patient-Reported Outcomes in Spinal Cord Stimulation"],"prefix":"10.1016","author":[{"given":"Mahir","family":"Kabir","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Theresa","family":"Medina","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sohail Rajesh","family":"Daulat","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marisa","family":"DiMarzio","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6488-9692","authenticated-orcid":false,"given":"Julie G.","family":"Pilitsis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.neurom.2026.06.464_bib1","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1200\/JCO.2015.63.0830","article-title":"Symptom monitoring with patient-reported outcomes during routine cancer treatment: a randomized controlled trial","volume":"34","author":"Basch","year":"2016","journal-title":"J Clin Oncol"},{"key":"10.1016\/j.neurom.2026.06.464_bib2","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1186\/1472-6963-13-211","article-title":"A systematic review of the impact of routine collection of patient reported outcome measures on patients, providers and health organisations in an oncologic setting","volume":"13","author":"Chen","year":"2013","journal-title":"BMC Health Serv Res"},{"key":"10.1016\/j.neurom.2026.06.464_bib3","doi-asserted-by":"crossref","first-page":"1539","DOI":"10.1016\/j.jval.2022.04.1724","article-title":"Toward system-wide implementation of patient-reported outcome measures: a framework for countries, states, and regions","volume":"25","author":"Ernst","year":"2022","journal-title":"Value Health"},{"key":"10.1016\/j.neurom.2026.06.464_bib4","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1177\/1355819617740925","article-title":"How do aggregated patient-reported outcome measures data stimulate health care improvement? A realist synthesis","volume":"23","author":"Greenhalgh","year":"2018","journal-title":"J Health Serv Res Policy"},{"key":"10.1016\/j.neurom.2026.06.464_bib5","doi-asserted-by":"crossref","first-page":"680","DOI":"10.1200\/CCI.20.00020","article-title":"Natural language processing to ascertain cancer outcomes from medical oncologist notes","volume":"4","author":"Kehl","year":"2020","journal-title":"JCO Clin Cancer Inform"},{"key":"10.1016\/j.neurom.2026.06.464_bib6","doi-asserted-by":"crossref","DOI":"10.1038\/tp.2015.182","article-title":"Predicting early psychiatric readmission with natural language processing of narrative discharge summaries","volume":"6","author":"Rumshisky","year":"2016","journal-title":"Transl Psychiatry"},{"key":"10.1016\/j.neurom.2026.06.464_bib7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1200\/CCI.18.00138","article-title":"Natural language processing for automated quantification of brain metastases reported in free-text radiology reports","volume":"3","author":"Senders","year":"2019","journal-title":"JCO Clin Cancer Inform"},{"key":"10.1016\/j.neurom.2026.06.464_bib8","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1037\/fsh0000584","article-title":"Harnessing the electronic health record to advance integrated care","volume":"39","author":"Zerden LdS","year":"2021","journal-title":"Fam Syst Health"},{"key":"10.1016\/j.neurom.2026.06.464_bib9","doi-asserted-by":"crossref","first-page":"243","DOI":"10.3171\/2020.11.SPINE201431","article-title":"Defining minimal clinically important differences in pain and disability outcomes of patients with chronic pain treated with spinal cord stimulation","volume":"35","author":"Sabourin","year":"2021","journal-title":"J Neurosurg Spine"},{"key":"10.1016\/j.neurom.2026.06.464_bib10","series-title":"Encyclopedia of Bioinformatics and Computational Biology","first-page":"546","article-title":"Performance measures for binary classification","author":"Berrar","year":"2019"},{"key":"10.1016\/j.neurom.2026.06.464_bib11","doi-asserted-by":"crossref","DOI":"10.1001\/jamanetworkopen.2024.44608","article-title":"Spinal cord stimulation vs medical management for chronic back and leg pain: a systematic review and network meta-analysis","volume":"7","author":"Huygen","year":"2024","journal-title":"JAMA Netw Open"},{"key":"10.1016\/j.neurom.2026.06.464_bib12","doi-asserted-by":"crossref","first-page":"6381","DOI":"10.2147\/JPR.S552361","article-title":"Real-world outcomes of spinal cord stimulation: a consecutive institutional experience with 505 trials, trial-to-implant ratio, long-term efficacy, and explantation risk factors","volume":"18","author":"Gheith","year":"2025","journal-title":"J Pain Res"},{"key":"10.1016\/j.neurom.2026.06.464_bib13","article-title":"A systematic review of evidence comparing spinal cord stimulation to sham or conservative medical management in the treatment of persistent spinal pain syndrome - type 2","volume":"4","author":"Glinka Przybysz","year":"2025","journal-title":"Interv Pain Med"},{"key":"10.1016\/j.neurom.2026.06.464_bib14","article-title":"ClinicalBERT: modeling clinical notes and predicting hospital readmission","author":"Huang","year":"2019","journal-title":"arXiv"},{"key":"10.1016\/j.neurom.2026.06.464_bib15","doi-asserted-by":"crossref","DOI":"10.1093\/jamiaopen\/ooaf026","article-title":"A deep learning model for clinical outcome prediction using longitudinal inpatient electronic health records","volume":"8","author":"Rong","year":"2025","journal-title":"JAMIA Open"},{"key":"10.1016\/j.neurom.2026.06.464_bib16","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1038\/s41746-021-00455-y","article-title":"Med-BERT: pretrained contextualized embeddings on large-scale structured electronic health records for disease prediction","volume":"4","author":"Rasmy","year":"2021","journal-title":"NPJ Digit Med"},{"key":"10.1016\/j.neurom.2026.06.464_bib17","doi-asserted-by":"crossref","DOI":"10.1259\/bjr.20220769","article-title":"Transformer versus traditional natural language processing: how much data is enough for automated radiology report classification?","volume":"96","author":"Yang","year":"2023","journal-title":"Br J Radiol"},{"key":"10.1016\/j.neurom.2026.06.464_bib18","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1016\/0885-3924(92)90064-O","article-title":"Comprehensive and multidimensional assessment and measurement of pain","volume":"7","author":"McGuire","year":"1992","journal-title":"J Pain Symptom Manage"},{"key":"10.1016\/j.neurom.2026.06.464_bib19","doi-asserted-by":"crossref","first-page":"565","DOI":"10.1097\/ACO.0000000000000225","article-title":"Acute pain assessment tools: let us move beyond simple pain ratings","volume":"28","author":"Gordon","year":"2015","journal-title":"Curr Opin Anaesthesiol"},{"key":"10.1016\/j.neurom.2026.06.464_bib20","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1370\/afm.250068","article-title":"Educating medical trainees about patient-centered documentation in the time of open notes","volume":"24","author":"Fleming","year":"2026","journal-title":"Ann Fam Med"},{"key":"10.1016\/j.neurom.2026.06.464_bib21","first-page":"E245","article-title":"Automated extraction of pain symptoms: a natural language approach using electronic health records","volume":"25","author":"Dave","year":"2022","journal-title":"Pain Physician"},{"key":"10.1016\/j.neurom.2026.06.464_bib22","doi-asserted-by":"crossref","first-page":"301","DOI":"10.7326\/M14-2128","article-title":"Clinical documentation in the 21st century: executive summary of a policy position paper from the American College of Physicians","volume":"162","author":"Kuhn","year":"2015","journal-title":"Ann Intern Med"},{"key":"10.1016\/j.neurom.2026.06.464_bib23","doi-asserted-by":"crossref","DOI":"10.2196\/52190","article-title":"Traditional machine learning, deep learning, and BERT (large language model) approaches for predicting hospitalizations from nurse triage notes: comparative evaluation of resource management, large language model","volume":"3","author":"Patel","year":"2024","journal-title":"JMIR Ai"},{"key":"10.1016\/j.neurom.2026.06.464_bib24","doi-asserted-by":"crossref","first-page":"127","DOI":"10.11648\/j.ajtas.20241305.13","article-title":"Comparative analysis of cross-validation techniques: LOOCV, K-folds cross-validation, and repeated K-folds cross-validation in machine learning models","volume":"13","author":"Lumumba","year":"2024","journal-title":"Am J Theor Appl Stat"}],"container-title":["Neuromodulation: Technology at the Neural Interface"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1094715926006240?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1094715926006240?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T20:50:09Z","timestamp":1785358209000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1094715926006240"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":24,"alternative-id":["S1094715926006240"],"URL":"https:\/\/doi.org\/10.1016\/j.neurom.2026.06.464","relation":{},"ISSN":["1094-7159"],"issn-type":[{"value":"1094-7159","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Proof of Concept of Natural Language Processing in Predicting Patient-Reported Outcomes in Spinal Cord Stimulation","name":"articletitle","label":"Article Title"},{"value":"Neuromodulation: Technology at the Neural Interface","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neurom.2026.06.464","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 International Neuromodulation Society. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}]}}