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Author

Shangqiguo Wang

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Open access Oct 2026

Audiologist-Guided Multimodal AI for Pure-Tone Audiometry and Tympanometry Interpretation and Reporting

Multimodal artificial intelligence (AI) could support audiology reporting, but an end-to-end score can obscure whether errors arise from image transcription, specialty-rule execution, or communication. We evaluated these as separate modules in 155 de-identified outpatient records representing 151 patients. In Module 1,...

Xia Wu, Xiao-Li Shen, Chang-Geng Mo et al. · 0 citations
Open access Aug 2026

From policy debate to empirical evidence: a proof-of-concept bibliometric and LLM-assisted abstract-level content analysis of OTC hearing aid research before and after FDA regulation.

OBJECTIVE To characterise temporal patterns in over-the-counter (OTC) hearing-aid research before and after U.S. Food and Drug Administration (FDA) implementation of the OTC category (effective October 2022), using bibliometrics and large language model (LLM)-assisted abstract-level annotation. DESIGN Bibliometric an...

Chang-Geng Mo, V. Manchaiah, J. Wasmann et al. · 0 citations
Review Open access Sep 2026

Evaluating Large Language Models in Clinical Audiology (AUDIOLOGYBENCH): Benchmark Development and Validation Study

Current frontier LLMs show strong recommendation generation but substantial limitations in audiometric numerical interpretation that are shared across models and that an automated adjudicator partially miscalibrated at the per-item level.

Lin-Kai Li, Chang-Geng Mo, Hao-Shuai Zhou et al. · 1 citation
#artificial intelligence Preprint Sep 2026

A bilingual AI audiologist built through rubric-guided playbook induction outperforms human audiologists in a blinded evaluation of simulated cases

A bilingual AI audiologist pairing a general-purpose large language model with rubric-guided playbook induction, multimodal audiogram interpretation and retrieval-augmented grounding, without fine-tuning the language-model backbone is presented.

Lin-Kai Li, Chang-Geng Mo, Han-Lin Yu et al. · 0 citations
Review Aug 2026

Development of the Mandarin Version of the Hearing and Functioning in Everyday Life Questionnaire.

The HFEQ-Mandarin is a promising tool for assessing daily hearing-related functioning in Mandarin-speaking adults and is a promising tool for assessing daily hearing-related functioning in Mandarin-speaking adults.

Shangqiguo Wang, Zhi-Hong Zheng, Li-Ping Zhang et al. · 0 citations

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