@article {Rassam2022387,
	title = {Empirical Study: What is the Best N-Gram Graphical Indexing Technique},
	journal = {Lecture Notes in Networks and Systems},
	volume = {489 LNNS},
	year = {2022},
	note = {cited By 0},
	pages = {387-398},
	abstract = {Recent research shows that indexing techniques, such as n-gram models, are useful at a wide variety of software engineering tasks, e.g., data extraction, document indexing, etc. However, these models require some numerous parameters. Moreover, the different ways one can extract data essentially yield different models. In this paper, we focus on n-gram models and evaluate how the use different set of methods and n values impact the predicting ability of these models. Thus, we compare the use of multiple techniques and sets of different parameters (n values character gram and word gram) with the aim of identifying the most appropriate indexing technique. {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.},
	doi = {10.1007/978-3-031-07969-6_29},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135074852\&doi=10.1007\%2f978-3-031-07969-6_29\&partnerID=40\&md5=76e738e6a8c5330d57d78e968047e57f},
	author = {Rassam, L. and Zellou, A. and Rachad, T.}
}
@article {ElHafidy2021,
	title = {Gamified mobile applications for improving driving behavior: A systematic mapping study},
	journal = {Mobile Information Systems},
	volume = {2021},
	year = {2021},
	note = {cited By 4},
	abstract = {Many research works and official reports approve that irresponsible driving behavior on the road is the main cause of accidents. Consequently, responsible driving behavior can significantly reduce accidents{\textquoteright} number and severity. Therefore, in the research area as well as in the industrial area, mobile technologies are widely exploited in assisting drivers in reducing accident rates and preventing accidents. For instance, several mobile apps are provided to assist drivers in improving their driving behavior. Recently and thanks to mobile cloud computing, smartphones can benefit from the computing power of servers in the cloud for executing machine learning algorithms. Therefore, many mobile applications of driving assistance and control are based on machine learning techniques to adjust their functioning automatically to driver history, context, and profile. Additionally, gamification is a key element in the design of these mobile applications that allow drivers to develop their engagement and motivation to improve their driving behavior. To have an overview concerning existing mobile apps that improve driving behavior, we have chosen to conduct a systematic mapping study about driving behavior mobile apps that exist in the most common mobile apps repositories or that were published as research works in digital libraries. In particular, we should explore their functionalities, the kinds of collected data, the used gamification elements, and the used machine learning techniques and algorithms. We have successfully identified 220 mobile apps that help to improve driving behavior. In this work, we will extract all the data that seem to be useful for the classification and analysis of the functionalities offered by these applications. {\textcopyright} 2021 Abderrahim El hafidy et al.},
	keywords = {Accidents, Computing power, Digital libraries, Driving assistance, Driving behavior, Gamification, Industrial area, Industrial research, Learning algorithms, Machine learning, Machine learning techniques, Mapping, Mobile applications, Mobile cloud computing, Mobile computing, Mobile Technology, Systematic mapping studies},
	doi = {10.1155/2021/6677075},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114117887\&doi=10.1155\%2f2021\%2f6677075\&partnerID=40\&md5=6ad1b624deabb49917039716eb133f13},
	author = {El Hafidy, A. and Rachad, T. and Idri, A. and Zellou, A.}
}
@article {Kharbouch2021,
	title = {Mobile Technology for Improved Contraceptive Care in Morocco},
	journal = {Journal of Medical Systems},
	volume = {45},
	number = {2},
	year = {2021},
	note = {cited By 0},
	abstract = {The fulfillment of unmet needs for contraception can help women reach their reproductive goals. Therefore, there is a growing concern worldwide about contraception and women{\textquoteright}s knowledge of making an advised choice about it. In this aspect, an outgrown number of apps are now available providing information concerning contraception whether it concerns natural contraception or modern contraception. However, vast amounts of these apps contain inaccurate sexual health facts and non-evidence-based information concerning contraception. On these bases, and in respect to: (1) the needs of women to effectively prevent unintended pregnancies while conducting a stress-free healthy lifestyle. (2) the World Health Organization (WHO) Medical Eligibility Criteria (MEC) for contraception{\textquoteright}s recommendations, and (3) the results/recommendations of a field study conducted in the reproductive health center {\textquoteleft}Les Orangers{\textquoteright} in Rabat to collect the app{\textquoteright}s requirements, we developed an evidence-based patient-centered contraceptive app referred to as {\textquoteleft}MyContraception{\textquoteright}. Thereafter, we conducted a set of functional tests to ensure that the MyContraception solution is performing as expected and is conform to the software functional requirements previously set before moving to non-functional requirements evaluation. Since customer{\textquoteright}s feedback is valuable to non-functional testing, we choose to evaluate potential users{\textquoteright} feedback. Moreover, giving that mobile app testing is a complex process involving different skill sets, we elaborated a rigorous experimental design to conduct an empirical evaluation of the MyContraception solution, which will exhaustively assess the overall quality of this solution and examine its effects on improving the quality of patient-centered contraception care. {\textcopyright} 2021, Springer Science+Business Media, LLC, part of Springer Nature.},
	keywords = {adult, Article, awareness, contraception, contraceptive agent, Contraceptive Agents, contraceptive behavior, eligibility criteria, evidence based practice center, experimental design, female, female fertility, field study, health care quality, healthy lifestyle, human, Humans, injectable contraceptive agent, long-acting reversible contraception, luteinizing hormone, menstrual cycle, Methodology, mobile application, Mobile applications, Morocco, oral contraceptive agent, patient care, pill, pregnancy, prescription, Privacy, questionnaire, reliability, reproductive health, risk factor, sexual health, technology, unplanned pregnancy, women{\textquoteright}s health, World Health Organization},
	doi = {10.1007/s10916-020-01684-6},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099086862\&doi=10.1007\%2fs10916-020-01684-6\&partnerID=40\&md5=91a540c873cdd78725ec3f6987f5b90f},
	author = {Kharbouch, M. and Idri, A. and Rachad, T. and Alami, H. and Redman, L. and Stelate, Y.}
}
@article {Bachiri202036,
	title = {A Complete Prenatal Solution for a Reproductive Health Unit in Morocco},
	journal = {Advances in Intelligent Systems and Computing},
	volume = {1161 AISC},
	year = {2020},
	note = {cited By 0},
	pages = {36-43},
	abstract = {A prenatal mobile Personal Health Records (mPHR), along with an Electronic Health Records (EHR) are, respectively, exploited in order to permit both the pregnant women and gynecologists or obstetricians monitor the pregnancy progress in the best conditions. For this intent, a complete solution consisting of a prenatal mPHR and an EHR were developed for the maternity {\textquotedblleft}Les Orangers{\textquotedblright} of the Avicenne University Hospital in Rabat. The complete solution provides the main functionalities of a prenatal service. Thereafter, the solution will be validated by conducting an experiment for quality and potential assessment. Hence, a recruitment process has been determined to identify the eligibility criteria to enroll participants (pregnant women and gynecologists), in addition to planning the course of the experiment. {\textcopyright} 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.},
	keywords = {Complete solutions, electronic health record, Eligibility criterion, Health, Information systems, Information use, Personal health record, Pregnant woman, Recruitment process, reproductive health},
	doi = {10.1007/978-3-030-45697-9_4},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085481969\&doi=10.1007\%2f978-3-030-45697-9_4\&partnerID=40\&md5=e3d4adffd953495adbfb14b0d483c067},
	author = {Bachiri, M. and Idri, A. and Rachad, T. and Alami, H. and Redman, L.M.}
}
@article {Sardi2020931,
	title = {Gamified e-Health Solution to Promote Postnatal Care in Morocco},
	journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
	volume = {12252 LNCS},
	year = {2020},
	note = {cited By 0},
	pages = {931-946},
	abstract = {The postnatal period is a critical phase in both the lives of the mothers and the newborns. Due to all the inherent changes that occur during this period, quality care is crucial during this period to enhance the wellbeing of the mothers and the newborns. In Morocco, the neglection of postnatal care services are often associated to poor communication, financial difficulties and cultural barriers. Mobile technology constitutes therefore a promising approach to bridge this gap and promote postnatal care. In order to improve the effectiveness of mobile technology, gamification has become a powerful feature to boost motivation and induce fun and interactivity into the mobile solutions{\textquoteright} tasks. Based on a previous review on mobile applications for postnatal care available in app repositories, a set of requirements have been identified to build a comprehensive mobile solution that cater the needs of both the mothers and the newborns. These requirements have, then, been enriched with real needs elicited at maternity Les orangers that belongs to the University Hospital Avicenne of Rabat. Along with the functional and non-functional requirements, gamification aspects have been also analyzed. After the analysis and design phases, a pilot version of the solution called {\textquoteleft}Mamma\&Baby{\textquoteright} has been implemented using android framework. {\textquoteleft}Mamma\&Baby{\textquoteright} is a mobile solution dedicated to assist new mothers during their postnatal period. As future work, it is expected to fully integrate the gamification elements into the solution and conduct an empirical evaluation of the overall quality and the potential of the solution with real puerperal women. {\textcopyright} 2020, Springer Nature Switzerland AG.},
	keywords = {E-health solutions, Empirical evaluations, Financial difficulties, Gamification, Mobile applications, Mobile solutions, Mobile Technology, Non-functional requirements, Overall quality, Quality control, Telecommunication equipment},
	doi = {10.1007/978-3-030-58811-3_66},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092252943\&doi=10.1007\%2f978-3-030-58811-3_66\&partnerID=40\&md5=2a3490959b88f98611929a0ad0efd78b},
	author = {Sardi, L. and Idri, A. and Rachad, T. and Redman, L. and Alami, H.}
}
@article {Rachad2020,
	title = {Intelligent Mobile Applications: A Systematic Mapping Study},
	journal = {Mobile Information Systems},
	volume = {2020},
	year = {2020},
	note = {cited By 3},
	abstract = {Smart mobiles as the most affordable and practical ubiquitous devices participate heavily in the enhancement of our daily life by the use of many convenient applications. However, the significant number of mobile users in addition to their heterogeneity (different profiles and contexts) obligates developers to enhance the quality of their apps by making them more intelligent and more flexible. This is realized mainly by analyzing mobile user{\textquoteright}s data. Machine learning (ML) technology provides the methodology and techniques needed to extract knowledge from data to facilitate decision-making. Therefore, both developers and researchers affirm the benefits of combining ML techniques and mobile technology in several application fields as e-health, e-learning, e-commerce, and e-coaching. Thus, the purpose of this paper is to have an overview of the use of ML techniques in the design and development of mobile applications. Therefore, we performed a systematic mapping study of papers published on this subject in the period between 1 January 2007 and 31 December 2019. A total number of 71 papers were selected, studied, and analyzed according to the following criteria, year, sources and channel of publication, research type, and methods, kind of collected data, and finally adopted ML models, tasks, and techniques. {\textcopyright} 2020 Taoufik Rachad and Ali Idri.},
	keywords = {Application fields, Decision making, Design and Development, Mapping, Methodology and techniques, Mobile applications, Mobile commerce, Mobile computing, Mobile Technology, Mobile users, Systematic mapping studies, Ubiquitous devices},
	doi = {10.1155/2020/6715363},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083095554\&doi=10.1155\%2f2020\%2f6715363\&partnerID=40\&md5=d474ab3cece2179d34f54fa7087a4cfb},
	author = {Rachad, T. and Idri, A.}
}
@article {Kharbouch202086,
	title = {MyContraception: An Evidence-Based Contraception mPHR for Better Contraceptive Fit},
	journal = {Advances in Intelligent Systems and Computing},
	volume = {1161 AISC},
	year = {2020},
	note = {cited By 1},
	pages = {86-94},
	abstract = {The fulfillment of unmet needs for contraception can help women reach their reproductive goals. It was proven to have a significant impact on reducing the rates of unintended pregnancies, and thereby cut the number of morbidity and mortality resulting from these pregnancies, and improving the lives of women and children in general. Therefore, there is a growing concern worldwide about contraception and women{\textquoteright}s knowledge of making an advised-choice about it. In this aspect, an outgrown number of apps are now available providing clinical resources, digital guides, or educational information concerning contraception whether it concerns natural contraception or modern contraception. However, vast amounts of these apps contain inaccurate sexual health facts and non-evidence based information concerning contraception. On these bases, and in respect to the needs of women to effectively prevent unintended pregnancies while conducting a stress-free healthy lifestyle, the World Health Organization (WHO) Medical Eligibility Criteria (MEC) for contraception{\textquoteright}s recommendations, and the results and recommendations of a field study conducted in the reproductive health center Les Oranges in Rabat to collect the app{\textquoteright}s requirements, we developed an Android app named {\textquoteleft}MyContraception{\textquoteright}. Our solution is an evidence-based patient-centered contraceptive app that has been developed in an attempt to facilitate: (1) Seeking evidence-based information along with recommendations concerning the best contraceptive fit (according to one{\textquoteright}s medical characteristics, preferences and priorities) helping users make informed decisions about their contraceptive choices. (2) Monitoring one{\textquoteright}s own menstrual cycle, fertility window, contraceptive methods usage, and the correlation between these different elements and everyday symptoms in one app. (3) Keeping record of one{\textquoteright}s family medical history, medical appointments, analyses, diagnoses, procedures and notes within the same app. In future work, conducting an empirical evaluation of MyContraception solution is intended, to exhaustively examine the effects of this solution in improving the quality of patient-centered contraception care. {\textcopyright} 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.},
	keywords = {Clinical resources, Diagnosis, Eligibility criterion, Empirical evaluations, Healthy lifestyles, Information concerning, Information systems, Information use, Informed decision, Obstetrics, reproductive health, World Health Organization},
	doi = {10.1007/978-3-030-45697-9_9},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085491736\&doi=10.1007\%2f978-3-030-45697-9_9\&partnerID=40\&md5=18f9987c1855619561fe9cc080957ade},
	author = {Kharbouch, M. and Idri, A. and Rachad, T. and Alami, H. and Redman, L. and Stelate, Y.}
}
