Abstract

Neurodegenerative disorders, such as Alzheimer’s and Parkinson’s, constitute a major factor in long-term disability and are becoming more and more a serious concern in developed countries. As there are, at present, no effective therapies, early diagnosis along with avoidance of misdiagnosis seem to be critical in ensuring a good quality of life for patients. In this sense, the adoption of computer-aided-diagnosis tools can offer significant assistance to clinicians. In this work, we provide in the first place a comprehensive recording of medical examinations relevant to those disorders. Then, a review is conducted concerning the use of Machine Learning techniques in supporting diagnosis of neurodegenerative diseases, with reference to at times used medical datasets. Special attention has been given to the field of Deep Learning. In addition to that, we communicate the launch of a newly created dataset for Parkinson’s disease, containing paraclinical data (925 Dat Scan images and 41,528 MRI images of 78 subjects in total -55 patients and 23 non-patients-), clinical data and epidemiological and treatment data for Parkinson's Disease prediction.  

How to acquire the data

If you want access to the dataset, email me at: d.kollias@qmul.ac.uk from your official academic email (as data cannot be released to personal emails) with subject: Parkinson's dataset request and include your job/title and official academic website in the email body.

References:

If you use the above data, you must cite the following papers:
 

• D. Kollias, et. al.: “Deep neural architectures for prediction in healthcare”, CIS, 2018 

@article{kollias2018deep, title={Deep neural architectures for prediction in healthcare}, author={Kollias, Dimitrios and Tagaris, Athanasios and Stafylopatis, Andreas and Kollias, Stefanos and Tagaris, Georgios}, journal={Complex \& Intelligent Systems}, volume={4}, number={2}, pages={119–131}, year={2018}, publisher={Springer}}

• A. Tagaris, et. al.: “Machine Learning for Neurodegenerative Disorder Diagnosis - Survey of Practices and Launch of Benchmark Dataset”, IJAIT, 2018 

@article{tagaris2018machine, title={Machine learning for neurodegenerative disorder diagnosis—survey of practices and launch of benchmark dataset}, author={Tagaris, Athanasios and Kollias, Dimitrios and Stafylopatis, Andreas and Tagaris, Georgios and Kollias, Stefanos}, journal={International Journal on Artificial Intelligence Tools}, volume={27}, number={03}, pages={1850011}, year={2018}, publisher={World Scientific}}

• A. Tagaris, et. al.: “Assessment of parkinson’s disease based on deep neural networks”, EANN, 2017

@inproceedings{tagaris2017assessment, title={Assessment of parkinson’s disease based on deep neural networks}, author={Tagaris, Athanasios and Kollias, Dimitrios and Stafylopatis, Andreas}, booktitle={Engineering Applications of Neural Networks: 18th International Conference, EANN 2017, Athens, Greece, August 25--27, 2017, Proceedings}, pages={391--403}, year={2017}, organization={Springer}}