What is it about?
This is a work that deals with the study of Parkinson disease employing application of machine learning in an automated model for early diagnosis of the disease. In this study, we used basic image preparation techniques and a BPNN on DAT imaging datasets from the Parkinson’s Progression Markers Initiative. 1,334 PD and 212 normal control (NC) subjects were included for the study.
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Why is it important?
The work is so important because of the difficulty faced in early detection of the parkinson disease.
Perspectives
My own personal perspective is that this work will help and support researches globally to be able to understand how to diagnose parkinson diseases in its early stages.
Pwadubashiyi Coston Pwavodi
Read the Original
This page is a summary of: High-accuracy Automated Diagnosis of Parkinson's Disease, Current Medical Imaging Formerly Current Medical Imaging Reviews, July 2020, Bentham Science Publishers,
DOI: 10.2174/1573405615666190620113607.
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