Machine Learning Algorithm to Detect Neurological Disorder

Abnormalities of brain is the main concern for healthcare industries, if it is not recognized or treated may lead to sever brain death. Neurological disorder such as epilepsy is slower and requires constant diagnosis and treatment. With the advent of recent technology physiologists are using x-rays, EEG, CT and MRI for early detection of such disorders. The diagnosis is accomplished by implementing machine learning techniques which aid in proper treatment. In this paper signals are acquired using electroencephalogram, a technique, that consists of parameters to classify different neurological disorders such as anxiety, epilepsy spikes etc., For this purpose, Machine Learning algorithms is implemented to categorize, which performs the classification of different brain abnormalities especially on epilepsy. Accuracy seems to be 96.1 under Extra Tree Classifier. This act as the assisting platform for doctors, aimed at effective treatment.

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Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-10-08
DOI
https://doi.org/10.1051/itmconf/20257901020/pdf
Primary Topic
Brain Tumor Detection and Classification
Type
article
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article

Machine Learning Algorithm to Detect Neurological Disorder

M D Nandeesh, J.V Alamelu
Springer Link (Chiba Institute of Technology)
Brain Tumor Detection and Classification
article

Machine Learning Algorithm to Detect Neurological Disorder

M D Nandeesh, J.V Alamelu
article en

Abstract

Abnormalities of brain is the main concern for healthcare industries, if it is not recognized or treated may lead to sever brain death. Neurological disorder such as epilepsy is slower and requires constant diagnosis and treatment. With the advent of recent technology physiologists are using x-rays, EEG, CT and MRI for early detection of such disorders. The diagnosis is accomplished by implementing machine learning techniques which aid in proper treatment. In this paper signals are acquired using electroencephalogram, a technique, that consists of parameters to classify different neurological disorders such as anxiety, epilepsy spikes etc., For this purpose, Machine Learning algorithms is implemented to categorize, which performs the classification of different brain abnormalities especially on epilepsy. Accuracy seems to be 96.1 under Extra Tree Classifier. This act as the assisting platform for doctors, aimed at effective treatment.

Springer Link (Chiba Institute of Technology)
Good health and well-being
Openalex Percentile: Top 34%
Brain Tumor Detection and Classification
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Machine Learning Algorithm to Detect Neurological Disorder — M D Nandeesh, J.V Alamelu · Springer Link (Chiba Institute of Technology) (2025) | TGRS Research Map | TGRS