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August 15, 2025Journal of Al-Qadisiyah for Computer Science and MathematicsOpen Access

Artificial Intelligence-Based Diagnostic Methods for Otitis Media: A Review Paper

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Authors

MHMohammed Salah HusseinSASalwa Khalid AbdulateefKIK. A. Ibrahim

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Overview

This review highlights AI's role in improving diagnostic accuracy for otitis media, suggesting future advancements may resolve existing challenges.

Key Points

  • AI plays a crucial role in enhancing diagnostic precision for otitis media, particularly in children and adults with atopic conditions.
  • Notably, deep neural networks have shown remarkable success in otoscopy image analysis, increasing diagnostic accuracy significantly.
  • This review evaluated a wide range of studies that demonstrate machine learning techniques improving treatment planning for otitis media.
  • Despite advancements, challenges like limited dataset standardization and image quality issues persist, requiring further exploration.

Cite This Study

Hussein et al. (2025) studied this question.

synapsesocial.com/papers/68a3656a0a429f797332b94bhttps://doi.org/10.29304/jqcsm.2025.17.22174
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Artificial Intelligence in Otitis Media Diagnosis: A Review of Diagnostic Accuracy, Limitations, Clinical Integration and Future Directions2025
  2. 2Deep Learning-Based Semantic Segmentation and Classification of Otoscopic Images for Otitis Media Diagnosis and Health Promotion2026
  3. 3A Soft Computing Approach for Efficient Diagnosis of Otitis Media Infection by Mucosal Disease Early Detection and Referrals2024 · 4 citations
  4. 4An artificial intelligence model for the diagnosis of otitis media with effusion in children2026
  5. 5Artificial intelligence in otolaryngology: current applications, limitations, and future perspectives2026