Sleep disorder is a disease that can be categorized as both an emotional and physical problem. It imposes several difficulties and problems, such as distress during the day, sleep-wake disorders, anxiety, and several other problems. Hence, the main objective of this research is to utilize the strong capabilities of machine learning in the prediction of sleep disorders. In specific, this research aims to meet three main objectives. These objectives are to identify the best regression model, the best classification model, and the best learning strategy that highly suits sleep disorder datasets. Considering two related datasets and several evaluation metrics that are related to the tasks of regression and classification, the results revealed the superiority of the MultilayerPerceptron, SMOreg, and KStar regression models compared with the other twenty-three regression models. Also, IBK, RandomForest, and RandomizableFilteredClassifier showed superior performance compared with other classification models that belong to several learning strategies. Finally, the Function learning strategy showed the best predictive performance among the six considered strategies in both datasets and with respect to the most evaluation metrics.

Mitochondrial dysfunctions remained a pivotal mechanism in manifold neurodegenerative diseases. Mitochondrial homeostasis within the cell is an essential aspect of cell biology. Mitochondria which is also known as the power-generating set of the cell, have a dominant role in several processes associated with the genomic integrity and cellular equilibrium maintenance. They are involved in maintaining optimal cells functioning and guidance from possible DNA damage which could lead to mutations and onset of diseases. Conversely, system perturbations which could be due to environmental factors or senescence induce changes in the physiological balance and result in the mitochondrial functions impairment. The focal point of this review focuses on mitochondrial dysfunction as a significant condition in the onset of neuronal disintegration. We explain the pathways associated with the dysfunction of the mitochondria which are common amongst the most recurring neurodegenerative diseases including Alzheimers and Parkinsons disease. Do mitochondrial dysfunctions represent an early event in causing a shift towards neuropathological processes?