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Revolutionizing Hearing Health: Mobile-based Audiometry Assessment Enhanced by Machine Learning Integration

P. KanimozhiP. JebaSanthiyaHoly cross Engineering College,Dept of Computer Science Engineering,Thoothukudi,Tamilnadu,IndiaT.Ananth KumarMohamed Inamul HussainChristo AnanthSamarkand State University,UzbekistanE. PreethiHoly cross Engineering College,Dept of Computer Science Engineering,Thoothukudi,Tamilnadu,India
2024en
ABI

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The Mobile-Based Audiometry Test Assessment with Machine Learning Integration is a user-friendly application for convenient and accurate hearing health assessment. This innovative app incorporates advanced machine learning algorithms to enhance the precision of hearing tests, allowing for early detection of hearing impairments. Users can effortlessly create profiles, securely store their test results, and access their hearing history. The application ensures the calibration of user hardware for accurate tests, closely mirroring clinical audiometry standards with a wide range of frequencies and decibel levels. Machine learning, particularly decision tree classification, is seamlessly integrated to improve the accuracy of audiogram analysis and classification, enabling the identification of varying degrees of hearing loss. The user-centric design and educational resources encourage awareness and proactive management of hearing health. This Mobile-Based Audiometry Test Assessment with Machine Learning Integration offers an accessible, technologically advanced solution for individuals to take charge of their auditory health and make informed decisions about their well-being.

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