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Phys. Eng. Express"],"published-print":{"date-parts":[[2026,8,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Wideband acoustic immittance (WAI) provides comprehensive frequency-dependent information for diagnosing middle ear pathologies. However, the scarcity of clinical data and complex response patterns significantly hinder automated diagnosis, particularly in data-limited scenarios. To address this issue, this study proposes a simulation-driven computer-aided diagnosis framework for WAI based on finite element (FE) modeling. Latin hypercube sampling was employed to systematically perturb key physiological parameters of the human ear FE models, generating a standardized virtual WAI dataset comprising 12 000 samples across the 0.2\u20136 kHz frequency range. The dataset includes four middle ear conditions: normal ear, ossicular chain discontinuity, ossicular chain fixation, and otitis media with effusion. Based on this dataset, a lightweight convolutional neural network tailored for multi-channel WAI inputs, termed WAIHybrid, was developed. It was benchmarked against traditional feature-based machine learning models and five representative deep learning architectures on simulated data and subsequently evaluated on an external clinical dataset comprising 206 ear-level WAI records. WAIHybrid achieved a macro-\n                    <jats:italic>F<\/jats:italic>\n                    1 of 96.30% and a balanced accuracy of 96.29% on an independent simulated test set. On the external clinical dataset, the corresponding values were 87.76% and 88.07%, respectively. Response-level comparisons, learned-representation analyses, and Integrated Gradients maps identified partial class-related correspondence between the simulated and clinical data, residual simulation-to-clinical discrepancy, and class-dependent channel\u2013frequency attribution patterns. These findings support a simulation-driven proof of concept for automated WAI analysis in data-limited middle ear assessment. Further evaluation in larger, more balanced, and clinically heterogeneous cohorts is needed.\n                  <\/jats:p>","DOI":"10.1088\/2057-1976\/ae885d","type":"journal-article","created":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T22:48:36Z","timestamp":1783637316000},"page":"045031","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Simulation-driven deep learning for the diagnosis of middle ear pathologies using wideband acoustic immittance"],"prefix":"10.1088","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-7380-335X","authenticated-orcid":true,"given":"Bochuan","family":"Jiang","sequence":"first","affiliation":[{"name":"China University of Mining and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chendong","family":"Li","sequence":"additional","affiliation":[{"name":"Anhui Medical University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiwei","family":"Guo","sequence":"additional","affiliation":[{"name":"Chinese PLA Medical School"},{"name":"National Clinical Research Center for Otolaryngologic Diseases"},{"name":"State Key Laboratory of Hearing and Balance Science"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanyan","family":"Chen","sequence":"additional","affiliation":[{"name":"Anhui Medical University"},{"name":"Chinese Academy of Sciences"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Zhao","sequence":"additional","affiliation":[{"name":"Huizhou University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wen","family":"Jiang","sequence":"additional","affiliation":[{"name":"Affiliated Hospital of Xuzhou Medical University"},{"name":"Xuzhou Medical University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Chen","sequence":"additional","affiliation":[{"name":"Chinese PLA Medical School"},{"name":"National Clinical Research Center for Otolaryngologic Diseases"},{"name":"State Key Laboratory of Hearing and Balance Science"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wen","family":"Liu","sequence":"additional","affiliation":[{"name":"Affiliated Hospital of Xuzhou Medical University"},{"name":"Xuzhou Medical University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5450-5958","authenticated-orcid":true,"given":"Houguang","family":"Liu","sequence":"additional","affiliation":[{"name":"China University of Mining and Technology"},{"name":"State Key Laboratory of Hearing and Balance Science"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2026,7,17]]},"reference":[{"key":"bpexae885dbib1","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1016\/j.otot.2024.01.001","type":"journal-article","article-title":"Contemporary mechanics of conductive hearing loss","volume":"35","author":"Remenschneider","year":"2024","journal-title":"Oper. 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