Diagnosis model for obstructive sleep apnea combining artificial immune system and logistic regression: A case study in Taiwan

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Obstructive Sleep Apnea (OSA) is a prevalent sleep disorder linked to serious health issues like cardiovascular diseases and diabetes.
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Polysomnography (PSG) is the gold standard for diagnosing OSA but is limited by cost, complexity, and patient compliance issues.
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Home Sleep Testing (HST) offers a less intrusive and more cost-effective alternative to PSG, though it provides limited physiological data.
4

This study developed a risk prediction model for OSA using an Artificial Immune System and Logistic Regression to enhance diagnostic accessibility.
5

The model incorporates simple questionnaires and physiological characteristics to improve OSA diagnosis in resource-limited settings.

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