Chapter title |
Identifying Parkinson’s Patients: A Functional Gradient Boosting Approach
|
---|---|
Chapter number | 39 |
Book title |
Artificial Intelligence in Medicine
|
Published in |
Artificial intelligence in medicine : 16th Conference on Artificial Intelligence in Medicine, Aime 2017, Vienna, Austria, June 21-24, 2017, Proceedings. Conference on Artificial Intelligence in Medicine (2005-) (16th : 2017 : Vienna, Au..., June 2017
|
DOI | 10.1007/978-3-319-59758-4_39 |
Pubmed ID | |
Book ISBNs |
978-3-31-959757-7, 978-3-31-959758-4
|
Authors |
Devendra Singh Dhami, Ameet Soni, David Page, Sriraam Natarajan |
Abstract |
Parkinson's, a progressive neural disorder, is difficult to identify due to the hidden nature of the symptoms associated. We present a machine learning approach that uses a definite set of features obtained from the Parkinsons Progression Markers Initiative(PPMI) study as input and classifies them into one of two classes: PD(Parkinson's disease) and HC(Healthy Control). As far as we know this is the first work in applying machine learning algorithms for classifying patients with Parkinson's disease with the involvement of domain expert during the feature selection process. We evaluate our approach on 1194 patients acquired from Parkinsons Progression Markers Initiative and show that it achieves a state-of-the-art performance with minimal feature engineering. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 17 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Doctoral Student | 4 | 24% |
Student > Ph. D. Student | 2 | 12% |
Researcher | 2 | 12% |
Student > Master | 1 | 6% |
Student > Bachelor | 1 | 6% |
Other | 0 | 0% |
Unknown | 7 | 41% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 3 | 18% |
Agricultural and Biological Sciences | 2 | 12% |
Philosophy | 1 | 6% |
Nursing and Health Professions | 1 | 6% |
Neuroscience | 1 | 6% |
Other | 2 | 12% |
Unknown | 7 | 41% |