International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | An Optimized Sleep Disorder Diagnosis Using Machine Learning Approaches |
|---|---|
| ABSTRACT | Sleep disorders such as insomnia and sleep apnea are growing public health concerns due to their impact on physical and mental well-being. Conventional diagnostic methods, including polysomnography, though accurate, are time-consuming, costly, and require clinical settings. The integration of machine learning (ML) and deep learning (DL) techniques has opened new avenues for automated, scalable, and cost-effective detection of sleep disorders. This paper presents a critical review of recent advancements in sleep disorder classification using ML and DL approaches. The reviewed studies utilize various data sources, including physiological signals and lifestyle attributes, applying methods such as feature extraction, hybrid model design, and ensemble learning. Algorithms like Random Forest, Support Vector Machines, and Convolutional Neural Networks demonstrate notable performance, with some achieving accuracies up to 99%. This review evaluates these models in terms of accuracy, robustness, and clinical relevance, while also addressing challenges such as data imbalance, computational complexity, and model interpretability. The findings aim to guide future research towards developing efficient, accurate, and interpretable systems for the early detection and diagnosis of sleep disorders. |
| AUTHOR | DR.N.DHIVYA, VAISHNAVY S Assistant Professor, Department of MCA, Vivekanandha Institute of Information and Management Studies, Tiruchengode, Namakal, Tamil Nadu, India. Department of MCA, Vivekanandha Institute of Information and Management Studies, Tiruchengode, Namakal, Tamil Nadu, India. |
| VOLUME | 184 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1405099 |
| pdf/99_An Optimized Sleep Disorder Diagnosis Using Machine Learning Approaches.pdf | |
| KEYWORDS | |
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