{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,20]],"date-time":"2025-09-20T19:25:12Z","timestamp":1758396312559,"version":"3.28.0"},"reference-count":34,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,12]]},"DOI":"10.1109\/bibm.2018.8621466","type":"proceedings-article","created":{"date-parts":[[2019,2,18]],"date-time":"2019-02-18T19:49:10Z","timestamp":1550519350000},"page":"2024-2030","source":"Crossref","is-referenced-by-count":12,"title":["Artificial Neural Networks Classification of Patients with Parkinsonism based on Gait"],"prefix":"10.1109","author":[{"given":"Carlos","family":"Fernandes","sequence":"first","affiliation":[]},{"given":"Luis","family":"Fonseca","sequence":"additional","affiliation":[]},{"given":"Flora","family":"Ferreira","sequence":"additional","affiliation":[]},{"given":"Miguel","family":"Gago","sequence":"additional","affiliation":[]},{"given":"Lus","family":"Costa","sequence":"additional","affiliation":[]},{"given":"Nuno","family":"Sousa","sequence":"additional","affiliation":[]},{"given":"Carlos","family":"Ferreira","sequence":"additional","affiliation":[]},{"given":"Joao","family":"Gama","sequence":"additional","affiliation":[]},{"given":"Wolfram","family":"Erlhagen","sequence":"additional","affiliation":[]},{"given":"Estela","family":"Bicho","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/0021-9290(95)00088-7"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.2522\/ptj.20050277"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1002\/mds.25674"},{"journal-title":"Deep learning Vol 1 Cambridge MIT press","year":"2016","key":"ref30"},{"key":"ref34","first-page":"222","article-title":"Scaling gait data to body size","volume":"3","year":"1996","journal-title":"Gait & Posture"},{"journal-title":"Eng Med Biol Soc","article-title":"Characterization of gait abnormalities in Parkinson&#x2019;s disease using a wireless inertial sensor system","year":"2010","key":"ref10"},{"key":"ref11","first-page":"1","article-title":"Comparative Motor Pre-clinical Assessment in Parkinson&#x2019;s Disease Using Supervised Machine Learning Approaches","year":"2018","journal-title":"Annals of Biomedical Engineering"},{"key":"ref12","first-page":"1","article-title":"Vertical ground reaction force marker for Parkinson&#x2019;s disease","volume":"12","year":"2017","journal-title":"PLoS ONE"},{"key":"ref13","first-page":"60065","article-title":"Statistical analysis of parkinson disease gait classification using Artificial Neural Network","year":"0","journal-title":"In Signal Processing and Information Technology (ISSPIT) 2011 IEEE International Symposium on"},{"key":"ref14","article-title":"Gait analysis: normal and pathological function","volume":"12","year":"1992","journal-title":"Journal of Pediatric Orthopaedics"},{"journal-title":"Data Mining Concepts and Techniques Elsevier","year":"2011","key":"ref15"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/BF00058655"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"ref18","first-page":"431","article-title":"Understanding variable importances in forests of randomized trees","year":"2013","journal-title":"In Advances in Neural Information Processing Systems"},{"journal-title":"TensorFlow Large-scale machine learning on heterogeneous systems 2015 Software available from","year":"0","key":"ref19"},{"year":"2017","key":"ref28","article-title":"A Python implementation of Deep Belief Networks built upon NumPy and TensorFlow with scikit-learn compatibility"},{"key":"ref4","article-title":"Early Parkinsonism: Distinguishing Idiopathic Parkinson&#x2019;s Disease from Other Syndromes","volume":"22","year":"2015","journal-title":"Jcom"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2013.05.025"},{"journal-title":"Parkinsonism & Related Disorders","article-title":"An updated diagnostic approach to subtype definition of vascular parkinsonism&#x2013;Recommendations from an expert working group","year":"2017","key":"ref3"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"180","DOI":"10.3923\/jas.2012.180.185","article-title":"Parkinson Disease Gait Classication based on Machine Learning Approach","volume":"12","year":"2012","journal-title":"Journal of Applied Sciences"},{"journal-title":"New York Springer","article-title":"Applied predictive modeling","year":"2013","key":"ref29"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1002\/mds.26693"},{"key":"ref8","article-title":"Automatic diagnosis of neuro-degenerative diseases using gait dynamics","volume":"45","year":"2012","journal-title":"Measurement"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2015.2450232"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1002\/mds.20083"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.icte.2016.10.005"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1002\/mds.25545"},{"journal-title":"Keras Github","article-title":"and others","year":"2015","key":"ref20"},{"key":"ref22","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","year":"2010","journal-title":"In Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics"},{"journal-title":"Pearson Upper Saddle River NJ USA","article-title":"Neural networks and learning machines","year":"2009","key":"ref21"},{"key":"ref24","first-page":"2013","article-title":"Review on methods to fix number of hidden neurons in neural networks","year":"2013","journal-title":"Mathematical Problems in Engineering"},{"journal-title":"arXiv preprint arXiv 1412 6980","article-title":"Adam: A method for stochastic optimization","year":"2014","key":"ref23"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2006.18.7.1527"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1561\/2200000006"}],"event":{"name":"2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","start":{"date-parts":[[2018,12,3]]},"location":"Madrid, Spain","end":{"date-parts":[[2018,12,6]]}},"container-title":["2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8609864\/8621069\/08621466.pdf?arnumber=8621466","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,23]],"date-time":"2020-08-23T23:26:17Z","timestamp":1598225177000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8621466\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,12]]},"references-count":34,"URL":"https:\/\/doi.org\/10.1109\/bibm.2018.8621466","relation":{},"subject":[],"published":{"date-parts":[[2018,12]]}}}