Abstract
Parkinson’s disease (PD), an intensifying neurological disorder is predominantly because of failing dopaminergic neurons of the midbrain. Dopamine is involved in sending of messages to those parts that controls coordination and movement in brain. With the help of Machine Learning approaches, it sets a base for an Intelligent system that helps in computer-aided diagnosis of PD patients. Machine Learning is used for early diagnosis and prediction so that it can be utilized to treat the disease quicker. In medicinal science, it is visible that outputs from the imaging devices can be incorporated for predicting a disease better. The paper specifies a brief synopsis of Machine Learning techniques along with MRI data which can yield faster prediction of PD.
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Naren, J., Ramalingam, P., Raja Rajeswari, U., Vijayalakshmi, P., Vithya, G. (2020). An Intelligent System on Computer-Aided Diagnosis for Parkinson’s Disease with MRI Using Machine Learning. In: Dehuri, S., Mishra, B., Mallick, P., Cho, SB., Favorskaya, M. (eds) Biologically Inspired Techniques in Many-Criteria Decision Making. BITMDM 2019. Learning and Analytics in Intelligent Systems, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-030-39033-4_16
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DOI: https://doi.org/10.1007/978-3-030-39033-4_16
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