{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T18:21:10Z","timestamp":1779906070903,"version":"3.53.1"},"reference-count":43,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,1,12]],"date-time":"2023-01-12T00:00:00Z","timestamp":1673481600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Tinnitus is a hearing disorder that is characterized by the perception of sounds in the absence of an external source. Currently, there is no pharmaceutical cure for tinnitus, however, multiple therapies and interventions have been developed that improve or control associated distress and anxiety. We propose a new Artificial Intelligence (AI) algorithm as a digital prognostic health system that models electroencephalographic (EEG) data in order to predict patients\u2019 responses to tinnitus therapies. The EEG data was collected from patients prior to treatment and 3-months following a sound-based therapy. Feature selection techniques were utilised to identify predictive EEG variables with the best accuracy. The patients\u2019 EEG features from both the frequency and functional connectivity domains were entered as inputs that carry knowledge extracted from EEG into AI algorithms for training and predicting therapy outcomes. The AI models differentiated the patients\u2019 outcomes into either therapy responder or non-responder, as defined by their Tinnitus Functional Index (TFI) scores, with accuracies ranging from 98%\u2013100%. Our findings demonstrate the potential use of AI, including deep learning, for predicting therapy outcomes in tinnitus. The research suggests an optimal configuration of the EEG sensors that are involved in measuring brain functional changes in response to tinnitus treatments. It identified which EEG electrodes are the most informative sensors and how the EEG frequency and functional connectivity can better classify patients into the responder and non-responder groups. This has potential for real-time monitoring of patient therapy outcomes at home.<\/jats:p>","DOI":"10.3390\/s23020902","type":"journal-article","created":{"date-parts":[[2023,1,12]],"date-time":"2023-01-12T05:45:33Z","timestamp":1673502333000},"page":"902","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Prediction of Tinnitus Treatment Outcomes Based on EEG Sensors and TFI Score Using Deep Learning"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4953-0662","authenticated-orcid":false,"given":"Maryam","family":"Doborjeh","sequence":"first","affiliation":[{"name":"Knowledge Engineering and Discovery Research Institute (KEDRI), School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, Auckland 1010, New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoxu","family":"Liu","sequence":"additional","affiliation":[{"name":"Knowledge Engineering and Discovery Research Institute (KEDRI), School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, Auckland 1010, New Zealand"},{"name":"Centre for Robotics & Vision (CeRV), Auckland University of Technology, Auckland 1010, New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1431-8258","authenticated-orcid":false,"given":"Zohreh","family":"Doborjeh","sequence":"additional","affiliation":[{"name":"Eisdell Moore Centre, Audiology, School of Population Health, The University of Auckland, Auckland 1010, New Zealand"},{"name":"School of Psychology, The University of Waikato, Hamilton 3216, New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuanyuan","family":"Shen","sequence":"additional","affiliation":[{"name":"Knowledge Engineering and Discovery Research Institute (KEDRI), School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, Auckland 1010, New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Grant","family":"Searchfield","sequence":"additional","affiliation":[{"name":"Eisdell Moore Centre, Audiology, School of Population Health, The University of Auckland, Auckland 1010, New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2511-3135","authenticated-orcid":false,"given":"Philip","family":"Sanders","sequence":"additional","affiliation":[{"name":"Eisdell Moore Centre, Audiology, School of Population Health, The University of Auckland, Auckland 1010, New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2063-031X","authenticated-orcid":false,"given":"Grace Y.","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Psychology and Wellbeing, University of Southern Queensland, Darling Heights, QLD 4350, Australia"},{"name":"Centre for Health Research, University of Southern Queensland, Darling Heights, QLD 4350, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4333-8442","authenticated-orcid":false,"given":"Alexander","family":"Sumich","sequence":"additional","affiliation":[{"name":"NTU Psychology, Nottingham Trent University, Nottingham NG1 4FQ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7443-3285","authenticated-orcid":false,"given":"Wei Qi","family":"Yan","sequence":"additional","affiliation":[{"name":"Centre for Robotics & Vision (CeRV), Auckland University of Technology, Auckland 1010, New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2331216518812250","DOI":"10.1177\/2331216518812250","article-title":"Why Is tinnitus a problem? 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