首页|Blekinge Institute of Technology Reports Findings in Dementia (Prediction of dementia based on older adults' sleep disturbances using machine learning)
Blekinge Institute of Technology Reports Findings in Dementia (Prediction of dementia based on older adults' sleep disturbances using machine learning)
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New research on Neurodegenerative Diseases and Conditions - Dementia is the subject of a report. According to news reporting originating from Blekinge, Sweden, by NewsRx correspondents, research stated, "The most common degenerative condition in older adults is dementia, which can be predicted using a number of indicators and whose progression can be slowed down. One of the indicators of an increased risk of dementia is sleep disturbances." Our news editors obtained a quote from the research from the Blekinge Institute of Technology, "This study aims to examine if machine learning can predict dementia and which sleep disturbance factors impact dementia. This study uses five machine learning algorithms (gradient boosting, logistic regression, gaussian naive Bayes, random forest and support vector machine) and data on the older population (60+) in Sweden from the Swedish National Study on Ageing and Care - Blekinge (n=4175). Each algorithm uses 10-fold stratified cross-validation to obtain the results, which consist of the Brier score for checking accuracy and the feature importance for examining the factors which impact dementia. The algorithms use 16 features which are on personal and sleep disturbance factors. Logistic regression found an association between dementia and sleep disturbances. However, it is slight for the features in the study. Gradient boosting was the most accurate algorithm with 92.9% accuracy, 0.926 f1-score, 0.974 ROC AUC and 0.056 Brier score. The significant factors were different in each machine learning algorithm. If the person sleeps more than two hours during the day, their sex, education level, age, waking up during the night and if the person snores are the variables that most consistently have the highest feature importance in all algorithms. There is an association between sleep disturbances and dementia, which machine learning algorithms can predict."
BlekingeSwedenEuropeAlgorithmsBrain Diseases and ConditionsCentral Nervous System Diseases and ConditionsCyborgsDementiaEmerging TechnologiesHealth and MedicineMachine LearningMental HealthNeurodegenerative Diseases and ConditionsRisk and Prevention
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