Intelligent Healthcare and Auditory Health: Machine Learning-Based Multimodal Biomedical Data Mining for Diagnosis

Dear Colleagues,

In the biomedical field, machine learning and data mining technologies are reshaping disease diagnosis, health monitoring, and rehabilitation at an unprecedented rate. This Special Issue focuses on the innovative applications of these cutting-edge technologies in disease diagnosis, health informatics, and speech and auditory health. It aims to establish an interdisciplinary platform that integrates medicine, engineering, and linguistics, and promotes the implementation of explainable AI in clinical auditory health.

Key research areas include:

• Auditory and Speech Health: Investigating the mechanisms of auditory information processing, enhancing the accuracy of speech recognition in noisy environments, and exploring speech biomarkers of neurodegenerative diseases (such as Alzheimer's disease) to provide critical evidence for early diagnosis and intervention.
• Intelligent Diagnostic Technologies: Integrating multimodal data from wearable devices, conducting multimodal medical imaging (e.g., fMRI combined with speech analysis), and advancing auditory rehabilitation engineering with biomechanics for precise healthcare.
• Public Health and Personalized Medicine: Developing early-screening tools for speech and auditory disorders, enabling tele-health monitoring and home-based screening via speech analysis, with a focus on ethical and privacy aspects of medical speech data to protect patients' interests.

The themes covered include, but are not limited to, the following:

• Auditory and Speech Computing: Optimizing cochlear implant parameters, refining noise suppression algorithms to enhance auditory signal processing and improve hearing-impaired individuals' auditory experiences.
• Speech Pathology Analysis: Analyzing speech characteristics of diseases like Alzheimer's and Parkinson's for new diagnostic and assessment angles.
• Multimodal Fusion: Integrating speech, EEG, and eye-movement data to decode neural activities and understand human cognitive and behavioral mechanisms.
• Intelligent Health Informatics: Extracting value from wearable auditory sensor data, building speech-based tele-health monitoring and home-screening systems, and strengthening speech and auditory epidemiological research in public health.
• Medical Diagnostic Engineering: Creating speech and auditory biomarker-based decision systems to boost computer-aided diagnosis; applying machine learning to optimize auditory rehabilitation devices like hearing aids and cochlear implants; exploring links between medical imaging and auditory pathways, mining auditory-related gene data, and modeling auditory perception neural mechanisms.

We invite researchers to submit their latest work to this Special Issue, promoting the development of machine learning and biomedical data mining in auditory health and advancing intelligent healthcare.

Dr. Meihong Wu
Dr. Yunfeng Wu
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• computer-aided diagnosis
• speech signal processing
• auditory information processing
• neurodegenerative diseases
• wearable devices
• health informatics
• multimodal fusion
• telemedicine, rehabilitation engineering
• noise-robust algorithms
• acoustic feature extraction
• cognitive impairment screening
• end-to-end speech enhancement