@article {Tougui2022210,
	title = {Machine Learning Smart System for Parkinson Disease Classification Using the Voice as a Biomarker},
	journal = {Healthcare Informatics Research},
	volume = {28},
	number = {3},
	year = {2022},
	note = {cited By 1},
	pages = {210-221},
	abstract = {Objectives: This study presents PD Predict, a machine learning system for Parkinson disease classification using voice as a biomarker. Methods: We first created an original set of recordings from the mPower study, and then extracted several audio features, such as mel-frequency cepstral coefficient (MFCC) components and other classical speech features, using a windowing procedure. The generated dataset was then divided into training and holdout sets. The training set was used to train two machine learning pipelines, and their performance was estimated using a nested subject-wise cross-validation approach. The holdout set was used to assess the generalizability of the pipelines for unseen data. The final pipelines were implemented in PD Predict and accessed through a prediction endpoint developed using the Django REST Framework. PD Predict is a two-component system: a desktop application that records audio recordings, extracts audio features, and makes predictions; and a server-side web application that implements the machine learning pipelines and processes incoming requests with the extracted audio features to make predictions. Our system is deployed and accessible via the following link: https://pdpredict. herokuapp.com/. Results: Both machine learning pipelines showed moderate performance, between 65\% and 75\% using the nested subject-wise cross-validation approach. Furthermore, they generalized well to unseen data and they did not overfit the training set. Conclusions: The architecture of PD Predict is clear, and the performance of the implemented machine learning pipelines is promising and confirms the usability of smartphone microphones for capturing digital biomarkers of disease. {\textcopyright} 2022 The Korean Society of Medical Informatics.},
	doi = {10.4258/hir.2022.28.3.210},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136283086\&doi=10.4258\%2fhir.2022.28.3.210\&partnerID=40\&md5=fe558706024fa51b7b86f00ad98e6bc4},
	author = {Tougui, I. and Jilbab, A. and El Mhamdi, J.}
}
@article {Anoual201227,
	title = {A novel texture-based algorithm for localizing vehicle license plates},
	journal = {Journal of Theoretical and Applied Information Technology},
	volume = {45},
	number = {1},
	year = {2012},
	note = {cited By 1},
	pages = {27-32},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84874531292\&partnerID=40\&md5=58ad16d91d008ad97e88e70a9234486f},
	author = {Anoual, H. and Fkihi, S.E. and Jilbab, A. and Aboutajdine, D.}
}
@conference {Bouirouga2011,
	title = {Recognition of adult video by combining skin detection features with motion information},
	booktitle = {International Conference on Multimedia Computing and Systems -Proceedings},
	year = {2011},
	note = {cited By 1},
	doi = {10.1109/ICMCS.2011.5945570},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79961239374\&doi=10.1109\%2fICMCS.2011.5945570\&partnerID=40\&md5=96e36065eca2afa2f2e3a18e0d2b4fe5},
	author = {Bouirouga, H. and Lrit, S.E. and Jilbab, A. and Aboutajdine, D.}
}
@conference {Anoual2011,
	title = {Vehicle license plate detection in images},
	booktitle = {International Conference on Multimedia Computing and Systems -Proceedings},
	year = {2011},
	note = {cited By 3},
	doi = {10.1109/ICMCS.2011.5945680},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79961227182\&doi=10.1109\%2fICMCS.2011.5945680\&partnerID=40\&md5=0640cc288461c0ff15b817b0c5d2a10b},
	author = {Anoual, H. and Fkihi, S.E. and Jilbab, A. and Aboutajdine, D.}
}
@conference {Bouirouga2010,
	title = {A comparison of skin detection techniques for objectionable videos},
	booktitle = {2010 5th International Symposium on I/V Communications and Mobile Networks, ISIVC 2010},
	year = {2010},
	note = {cited By 0},
	doi = {10.1109/ISVC.2010.5656278},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-78651520179\&doi=10.1109\%2fISVC.2010.5656278\&partnerID=40\&md5=cbf0bdbe507be5b0297aaf80e2b30d25},
	author = {Bouirouga, H. and El Fkihi, S. and Jilbab, A. and Bakrim, M.}
}
@conference {Anoual2010,
	title = {Features extraction for text detection and localization},
	booktitle = {2010 5th International Symposium on I/V Communications and Mobile Networks, ISIVC 2010},
	year = {2010},
	note = {cited By 1},
	doi = {10.1109/ISVC.2010.5656284},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-78651516449\&doi=10.1109\%2fISVC.2010.5656284\&partnerID=40\&md5=7432f9409c4d2e3bd7a3aa3a78c5865a},
	author = {Anoual, H. and Aboutajdine, D. and Elfkihi, S. and Jilbab, A.}
}
@article {Anoual2010157,
	title = {New approach based on texture and geometric features for text detection},
	journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
	volume = {6134 LNCS},
	year = {2010},
	note = {cited By 0},
	pages = {157-164},
	doi = {10.1007/978-3-642-13681-8_19},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79956278929\&doi=10.1007\%2f978-3-642-13681-8_19\&partnerID=40\&md5=c16c63472198a6944f7f472697a0cc7c},
	author = {Anoual, H. and El Fkihi, S. and Jilbab, A. and Aboutajdine, D.}
}
