Assessment of Neurological Disorders among Children using Machine Learning Techniques

 The early diagnosis of neurological problems in children helps medical personnel to enhance the patients’ health. Therefore, it is essential to recognise neurological anomalies since, if treatment is delayed, they might turn into major problems. Medical data may be analysed and the problem can be accurately diagnosed with the help of machine learning algorithms. This research has discovered machine learning algorithms on several accuracy metrics to accurately detect three prevalent neurological disorders. A neurological data set is collected from a neuro clinic facility in order to evaluate the efficacy of machine learning approaches. Numerous psychological examinations, including clinic neuropsychiatric observation, audio evaluation, and intellectual coefficient assessment, are also carried out on people who have neurological diseases. Some of the collected characteristics were found to be crucial for figuring out the problem. The findings unmistakably demonstrate that the chosen ML techniques produced results that were more accurate, and there is just a little variation in how well they performed.

Author(s) Details:

G. Reshma,
Department of Information Technology, PVPSIT, Kanuru, Vijayawada, India.

P. V. S Lakshmi,
Department of Information Technology, PVPSIT, Kanuru, Vijayawada, India.

Please see the link here: https://stm.bookpi.org/RDST-V10/article/view/7723

Keywords: Neurological disorders, machine learning, predictive analytics, feature subset selection

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