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The Design and Evaluation of a Simulation Tool for Audiology Screening Education: Design Science Approach

The Design and Evaluation of a Simulation Tool for Audiology Screening Education: Design Science Approach

However, the use of simulation in audiology education is still in its infancy compared to some other fields, such as nursing and medicine [3]. It can be challenging for speech-language pathology students to obtain the necessary audiology training due to limited practicum opportunities. One alternative is to use a commercial simulator application, such as Otis–the virtual patient [18], which is a simulator designed for use in the education of audiologists.

John Gerdes, Benjamin Schooley, Dakota Sharp, Juliana Miller

JMIR Form Res 2025;9:e47150

Explainable AI Method for Tinnitus Diagnosis via Neighbor-Augmented Knowledge Graph and Traditional Chinese Medicine: Development and Validation Study

Explainable AI Method for Tinnitus Diagnosis via Neighbor-Augmented Knowledge Graph and Traditional Chinese Medicine: Development and Validation Study

Tinnitus is a common refractory disease in the field of otolaryngology, and its diagnosis has always been a cutting-edge research topic in audiology. With changes in the social environment and an accelerated pace of life, an increasing number of patients, particularly among the younger generation, have sought medical assistance for tinnitus as their primary complaint in the last decade.

Ziming Yin, Zhongling Kuang, Haopeng Zhang, Yu Guo, Ting Li, Zhengkun Wu, Lihua Wang

JMIR Med Inform 2024;12:e57678

Exploring the Performance of ChatGPT-4 in the Taiwan Audiologist Qualification Examination: Preliminary Observational Study Highlighting the Potential of AI Chatbots in Hearing Care

Exploring the Performance of ChatGPT-4 in the Taiwan Audiologist Qualification Examination: Preliminary Observational Study Highlighting the Potential of AI Chatbots in Hearing Care

Chat GPT’s advanced capabilities position it as a potential tool for patient interaction, education, aural rehabilitation program, and preliminary diagnostics in audiology [18,19]. However, it is crucial to recognize its current limitations. While it can handle complex interactions, it is not a substitute for human expertise in specialized areas such as audiology and is limited in interpreting nuanced medical information or performing physical diagnostics.

Shangqiguo Wang, Changgeng Mo, Yuan Chen, Xiaolu Dai, Huiyi Wang, Xiaoli Shen

JMIR Med Educ 2024;10:e55595

Peer Review of “Cross-Modal Sensory Boosting to Improve High-Frequency Hearing Loss: Device Development and Validation”

Peer Review of “Cross-Modal Sensory Boosting to Improve High-Frequency Hearing Loss: Device Development and Validation”

For the audiometric data, how many participants provided their test results from a doctor of audiology or hearing health care professional? How many provided results from the mobile app? Is it possible to confirm that all participants had sensorineural hearing loss and not mixed or conductive hearing loss? In the Device subsection, consider adding additional information regarding the microphone characteristics. Additionally, define “GRMS.”

­ Anonymous

JMIRx Med 2024;5:e55727

Authors’ Response to Peer Reviews of “Cross-Modal Sensory Boosting to Improve High-Frequency Hearing Loss: Device Development and Validation”

Authors’ Response to Peer Reviews of “Cross-Modal Sensory Boosting to Improve High-Frequency Hearing Loss: Device Development and Validation”

For the audiometric data, how many participants provided their test results from a doctor of audiology or hearing health care professional? How many provided results from the mobile app? Is it possible to confirm that all participants had sensorineural hearing loss and not mixed or conductive hearing loss? Response: A total of 7 participants provided 2 audiograms from the online assessments (a Mimi hearing assessment), and 9 provided audiograms from an audiologist.

Izzy Kohler, Michael V Perrotta, Tiago Ferreira, David M Eagleman

JMIRx Med 2024;5:e55510