Bouchaib Cherradi

Centre Régional des Métiers de l'Education et de la Formation (CRMEF) d'El Jadida, Maroc. · Informatique

E-learning has emerged as a prominent educational method, providing accessible and flexible learning opportunities to students worldwide. This study aims to comprehensively understand and categorize learner performance on e-learning platforms, facilitating timely support and interventions for improved academic outcomes. The proposed model utilizes...

Age-related macular degeneration (AMD) is a degenerative retina condition that causes notable visual impairment in the central area of the visual field during its advanced stages. Manual segmentation of the retina layers and fluids in Optical coherence tomography (OCT) images is a dominant clinical practice but is time-consuming and labor-intensive...

Floods represent a significant natural hazard causing extensive damages. The research aims to demonstrate the robustness of employing Machine Learning (ML) models, namely Random Forest (RF), Support Vector Machine (SVM), Logistic Regression (LR), K-nearest neighbor (KNN), and Decision Tree (DT) to generate flood susceptibility maps for Tetouan city...

Parkinson's disease is a progressive neurodegenerative disorder that causes significant physical disabilities and reduces the quality of life. This disease is caused by the loss of dopamine-producing cells in the brain. Its symptoms are Speech disorders, muscle rigidity, bradykinesia and tremors that cause involuntary shaking or trembling, typicall...

With the advancements in technology and the growing demand for online education, Virtual Learning Environments (VLEs) have experienced rapid development in recent years. This demand was especially evident during the COVID-19 pandemic. The incorporation of new technologies in VLEs provides new opportunities to better understand the behaviors of lear...

The medical community has a significant interest in an accurate, reliable, and effective Medical Diagnosis Support System for COVID-19. Compared to the RT-PCR test, clinical database-based COVID-19 diagnosis has been proven to have superior sensitivity and specificity. Recent research has highlighted the benefits of Machine Learning and routine blo...

Data imbalance is a common challenge in machine learning, particularly in medical image analysis tasks such as skin disease prediction. Melanoma, a type of skin cancer, is a prime example of a rare disease where the number of positive cases (minority class) is significantly smaller than the negative cases (majority class). This imbalance can lead t...

The process of picking appropriate hyper-parameters for classification or prediction algorithms is a tough endeavor in the field of modeling. This selection is essential for the capacity for generalization and the performance of classifiers. Over the course of two tests, this article examines and evaluates the performance of five different Machine...

In order to effectively treat skin diseases, an accurate and prompt diagnosis is required. In this article, a novel method for classifying skin disorders using a multimodal classifier is presented. The proposed classifier utilizes multiple information sources to enhance the accuracy of disease classification. It incorporates images of skin lesions...

Skin disease prediction using artificial intelligence has shown great potential in improving early diagnosis and treatment outcomes. However, the presence of class imbalance within skin disease datasets poses a significant challenge for accurate prediction, particularly for rare diseases. This study proposes a novel approach to address class imbala...

Significant health concerns are associated with skin diseases, and accurate and timely diagnosis is essential for effective treatment and patient management. To improve the classification of cutaneous diseases, we propose a novel hybrid system that incorporates the strengths of random forest (RF) and deep neural network (DNN) algorithms. The system...

According to the World Health Organization (WHO), cardiovascular disease is one of the leading causes of death worldwide. Thus, the prevention of this kind of illness is considered as a huge human health challenge. Additionally, the diagnostic process often involves a combination of clinical examination, laboratory tests, and other diagnostic proce...

Due to the rapid propagation characteristic of the Coronavirus (COVID-19) disease, manual diagnostic methods cannot handle the large number of infected individuals to prevent the spread of infection. Despite, new automated diagnostic methods have been brought on board, particularly methods based on artificial intelligence using different medical da...

Computer-aided diagnosis (CAD) systems based on machine learning (ML) techniques have altered the field of medical research. The deployement of such models to classify breast cancer is one area of many where exactness has been the main preoccupation. CAD systems aim to reach the performance of trained clinicians in identifying breast cancer at its...

Parkinson’s disease is the second most common neurological disorder that causes significant physical disabilities, decreases the quality of life, and does not have a cure. Because it is a nervous system disorder, it impacts people in different ways, affecting movement and speech and causing muscle stiffness. Approximately, 90% of people with Parkin...

Realtime space weather activity tracking has improved over the years due to recent advancements in astronomical instrumentation. Sunspots are known as important phenomenon of sun and can be addressed on photosphere of sun surface. The occurrences of sunspots determine overall solar activities, sunspots are being observed from early eighteenth centu...

People crave interaction and connection with other people. Therefore, social media became the center of society’s life. Among the brightest social media platforms nowadays with a massive number of daily users there is Instagram, which is due to its distinctive features. The excessive revealing of personal life has put users in the spots of getting...

Skin diseases represent a variety of disorders that can affect the skin. In fact, early diagnosis plays a central role in the treatment of this type of disease. This scholarly article introduces a novel approach to classifying skin diseases by leveraging two ensemble learning techniques, encompassing multi-modal and multi-task methodologies. The pr...

Breast cancer is a significant medical and social issue that draws attention from the global scientific community. The classification of ultrasound images of breast cancer plays a crucial role in computer-aided diagnostic systems. In this paper, we present a deep learning technique for the diagnosis of breast cancer using ultrasound images. The pro...

breast cancer is the most spread cancer globally. The disease symptoms and treatments differ from one patient to another. Early detection can considerably alter the outcome for breast cancer patients. CAD systems play a fundamental role in the prognosis of the disease. In this paper, a proposed ensemble model based on the stacking technique uses lo...

E-platforms one of the most important solutions whose services must be provided for the education process to be more efficient and the fastest way to create an educational connection between professors and learners, in particularly in the difficult circumstances left by the Covid-19 pandemic. The e-learning or the new learning paradigm is a method...

The diagnosis of Colorectal and Rectum Cancer (CRC) is a global concern as it is the third most commonly diagnosed cancer. Early detection and treatment of polyps can prevent the development of colon cancer. To assist with this, Computed Tomography (CT) scans are used to produce three-dimensional images of the interior of the colon. Deep Learning t...

Questions classification is a crucial task in automatic question answering systems. In this paper, we present a system for classifying questions asked by students about higher studies and career choices based on their abilities and skills. The system uses natural language processing and machine learning techniques. We collected and labeled a datase...

Sentiment analysis is the field of determining the attitude or emotions expressed in text, which has become popular due to the rise of social media. AI, ML, and DL have greatly impacted the field of NLP and there have been efforts to improve the accuracy of sentiment analysis using linear models and deep neural networks. The analysis of emotions an...

Data balancing through data augmentation is a crucial step in improving the generalization of transfer learning for skin disease prediction. Many skin diseases, such as melanoma, are rare, and thus, the number of samples in the minority class is often limited. By using data augmentation techniques, the number of samples in the minority class can be...

Blockchain has attracted a lot of interest since its publication because to its unique characteristics of immutability, decentralization, smart contract, and consensus mechanism. Today's healthcare systems are facing many issues in the era of digital health transformation and the growth of electronic health records. Blockchain has the potential to...

Cyberbullying takes its place in social media and has increased throughout the past few years. The damage that cyberbullying has on the users is undeniable they get attacked either on their appearances, ethnicities, religions, and even their thoughts and personal opinion. The attack causes these users anxiety, depression, low self-esteem, and in th...

Cardiovascular disease is the leading cause of death worldwide, with 17.9 million deaths occurring annually. This disease an illness that affects the heart and blood vessels, and it has various consequences, including coronary artery disease, heart failure, stroke, and hypertension. Indeed, many factors that can contribute to cardiovascular disease...

Handwriting text recognition for computer systems has been the subject of more and more research. Recognition of Arabic handwritten text is always an ongoing challenge, mainly due to the similarity between its letters and various writing styles. However, the problem of cursive handwriting recognition remains laborious due to the complexity of the A...

Brain degeneration involves several neurological troubles such as Parkinson’s disease (PD). Since this neurodegenerative disorder has no known cure, early detection has a paramount role in improving the patient’s life. Researchhas shown that voice disorder is one of the first symptoms detected. The application of deep learning techniques to data ex...

In the last decade, healthcare systems have played an effective role in improving medical services by monitoring and diagnosing patients' health remotely. These systems, either in hospitals or in other health centers, have experienced significant growth with emerging technologies. They are becoming of great interest to many countries worldwide nowa...

Handwriting recognition is a multi-step process that includes data collection, preprocessing, feature extraction, and classification in order to create a final prediction. This process becomes more and more delicate when dealing with the scriptures of college or secondary school learners. The primary purpose of this research is to offer an improved...

In the context of COVID-19 pandemic, the Moroccan Interior and Health Ministries have proposed to use the health pass with a QR code to identify vaccinated people. Additionally, the government suggested a mobile application to control the health passport authenticity. However, the key problem is the possibility of anyone scanning the QR code and fi...

Digital Transformation has become one of the most discussed debates; many sectors have adopted digital transformation to gain a competitive advantage and to ensure their continuity. Moroccan universities, in their turn, are facing strategic and managerial challenges due to emerging practices related to digital transformation. To address this issue,...

Smart coaching and e-sport platforms have shown a great interest in the recent research studies. Through this study, we aim to globalize the practice of sport, especially Shotokan Karate, by connecting participants and coaches on an international scale through the integration of Artificial Intelligence techniques such as computer vision and deep le...

Arabic handwritten text recognition has long been a difficult subject, owing to the similarity of its characters and the wide range of writing styles. However, due to the intricacy of Arabic handwriting morphology, solving the challenge of cursive handwriting recognition remains difficult. In this paper, we propose a new efficient based image proce...

The computation of network reliability for a system with many states is an NP-hard issue. Finding all the minimum path vectors (d-MPs) lower boundary points for each level d is one of the few approaches for computing such dependability. This research proposed enhancements to the technique described in Chen's "Searching for d-MPs with rapid enumerat...

Many technological networks that execute their tasks with different levels of distinctive efficiency are multi-state systems, and reliability is an essential predicate for their safe operation and optimal improvement. In this paper, a survey of recent progress of the evaluation of exact reliability for multi-state system is presented. A general met...

To compute system reliability, many approaches are available in the literature. One of the most used approaches is the enumeration method, minimal paths or minimal cuts. Most of these approaches enumerate the minimal paths to evaluate reliability, but few of them used minimal cuts. This paper proposes a new direct method that enumerates all the min...

Detection of Parkinson’s disease remains challenge for physicians, especially, in the clinical field due to the difficulty of cure. Thus, algorithms of classification have the main role in the assessment of this neurodegenerative disorder. In this paper, we focus on the analysis and the evaluation of nine Machine Learning Algorithms (MLA), namely S...

Fuzzy C-mean (FCM) is an algorithm for data segmentation and classification, robust and very popular within the scientific community. It is used in several fields such as computer vision, medical imaging and remote control. The purpose of this paper is to propose a parallel implementation of the iterative type-2 fuzzy C-mean (IT2FCM) algorithm on a...

The current healthcare systems are facing many issues in terms of data management, data sharing, information security and patient privacy, data immutability, trust, and transparency. In addition, the multiple existing healthcare systems are centralized which complicates the healthcare professionals, patients in managing their data and causes severa...

Manual segmentation of brain tumors from MRI images is very frustrating and time consuming for medical doctors and relies on accurate segmentation of regions of interests. Convolutional neural networks (CNN)–based segmentation has gained a huge amount of attention over the last few years due to its speed and automated aspect. As the CNN models are...

The COVID19 infection was sparked by the severe acute respiratory syndrome SARS-CoV-2, as mentioned by the World Health Organization, and originated in Wuhan, Republic of China, eventually extending to every nation worldwide in 2020. This research aims to establish an efficient medical diagnosis support system (MDSS) for recognizing COVID19 in ches...

A brain tumor is the cause of abnormal growth of cells in the brain. Magnetic resonance imaging (MRI) is the most practical method for detecting brain tumors. Through these MRIs, doctors analyze and identify abnormal tissue growth and can confirm whether the brain is affected by a tumor or not. Today, with the emergence of artificial intelligence t...

Convolution Neural Network (CNN) models have gained ground in research activities particularly in medical images used for Diabetes Retinopathy (DR) detection. X-ray, MRI, and CT scans have all been used to validate CNN models, with classification accuracy generally reaching that of trained doctors. It is mandatory to evaluate the strength of CNN mo...

At present, most people prefer using different online sources for reading news. These sources can easily spread fake news for several malicious reasons. Detecting this unreliable news is an important task in the Natural Language Processing (NLP) field. Many governments and technology companies are engaged in this research field to prevent the manip...

Coronavirus (COVID-19) is the most prevalent coronavirus infection with respiratory symptoms such as fever, cough, dyspnea, pneumonia, and weariness being typical in the early stages. On the other hand, COVID-19 has a direct impact on the circulatory and respiratory systems as it causes a failure to some human organs or severe respiratory distress...

With daily increasing of suspected COVID-19 cases, the likelihood of the virus mutation increases also causing the appearance of virulent variants having a high level of replication. Automatic diagnosis methods of COVID-19 disease are very important in the medical community. An automatic diagnosis could be performed using machine and deep learning...

COVID-19 is an infectious disease-causing flu-like respiratory problem with various symptoms such as cough or fever, which in severe cases can cause pneumonia. The aim of this paper is to develop a rapid and accurate medical diagnosis support system to detect COVID-19 in chest X-ray images using a stacking approach combining transfer learning techn...

Parkinson’s disease (PD) is one of the most widespread diseases that, primarily, affects the motor system of the neural central system. In fact, PD is characterized by tremors, stiffness of the muscles, imprecise gait movements, and vocal impairment. An accurate diagnosis of Parkinson’s disease is usually based on many neurological, psychological,...

Nowadays, the biomedical signal processing area (MSP) is one of the most important research fields. It is often applied in medical diagnosis and early detection of neurological diseases. Thereby, the MSP is deployed in Parkinson’s disease (PD) detection from voice disorder. Therefore, Convolutional Neural Networks (CNN) and Artificial Neural Networ...

COVID-19 disease is similar to normal pneumonia caused by bacteria or other viruses. Therefore, the manual classification of lung diseases is very hard to discover, particularly the distinction between COVID-19 and NON-COVID-19 disease. COVID-19 causes infections on one or both lungs which appear as inflammations across lung cells. This can lead to...

Diabetic retinopathy (DR) is a complication that affects eyes and is one of the common causes of blindness in the developed world. With the adoption of unhealthy lifestyles and the number of diabetic patients is rising more rapidly, there is a growing need for an automated system for early diagnosis and treatment to avoid blindness. With the develo...

La problématique de l’évaluation des apprentissages au sein d’un MOOC suscite un grand débat. Ce type d’environnements d’apprentissage offre des cours limités dans le temps, organisés en ligne et ouverts à tous. L’apprentissage au sein des MOOC consiste en l’échange du savoir entre les participants et l’interaction avec les concepteurs (forum, chat...

La fraude aux examens scolaire a fait l’objet ces dernières années l’objet d’une forte médiatisation, en particulier à l’approche des examens. Par ailleurs, les enseignants se plaignent de plus en plus des apprenants et des étudiants qui utilisent leur téléphone pendant les épreuves. Avec l’arrivée de la technologie dans les classes et l’utilisatio...

Analysis and classification of lung diseases using X-ray images is a primary step in the procedure of pneumonia diagnosis, especially in a critical period as pandemic of COVID- 19 that is type of pneumonia. Therefore, an automatic method with high accuracy of classification is needed to perform classification of lung diseases due to the increasing...

The problems which arise in the system of automatic recognition of the handwritten Arabic script shows that the morphology complexity of the Arabic script and its cursivity remains a very vast subject of research. This research subject has known in recent years a great progress especially in the automation of postal mail sorting, check processing a...

Machine learning (ML) technique behind the most existing abilities fields in several areas like languages processing, robotics, including medicine. The most important medical applications are the early prediction system for heart diseases especially, coronary artery disease (CAD) also called atherosclerosis. The need for a medical diagnosis support...

Manual segmentation of brain tumors from MRI images is very frustrating and time consuming for medical doctors, and relies on accurate segmentation of regions of interests. Convolutional Neural Networks (CNN) based segmentation has gained a huge amount of attention over the last few years due to its speed and automated aspect. As the CNN models are...

In recent years, speech signal processing has benefited from a lot of attention, because of its widespread application. In this study, we have led a comparative analysis for efficient detection of Parkinson’s disease applied to machine learning classifiers from voice disorder known as dysphonia. To prove robust detection process, we used Artificial...

A healthcare system using modern computing techniques is the highest explored area in healthcare research. Researchers in the field of computing and healthcare are persistently working together to make such systems more technology ready. Diabetes is considered as one of the deadliest and chronic diseases it leads to complications such as blindness,...