All of the articles in this proceedings volume have been presented at The International Conference on Decision Aid and Artificial Intelligence (ICODAI) during 31 October 2024 in Tunis, Tunisia. These articles have been peer reviewed by the members of the Scientific Committee and approved by the Editor-in-Chief,...

AI models have been widely used as recommender systems in domains such as nutrition, medicine, health status prediction and physical activity. However, their application to drug recommendation is limited due to the complex nature of the medical data stored in Electronic Health Records (EHRs). Existing...

Systemic Lupus Erythematosus (SLE) is an autoimmune disease which can affect multiple organs in the human body. Many reasons are remaining as a factor for this disease such as environmental, hormonal and genetic factors. SLE diagnosis is complicated and is done following well-established classification...

Cerebral palsy (CP) is a complex neurodevelopmental disorder that necessitates precise diagnosis and personalized treatment to enhance patient outcomes. This paper examines the application of artificial intelligence (AI) and machine learning in CP diagnosis and treatment, focusing on current advancements...

Deep learning has transformed recommender systems by enabling them to thoroughly analyze and comprehend intricate patterns in user behavior and preferences. With the ability to handle large volumes of data, these systems can make accurate predictions and offer personalized suggestions in the healthcare...

In professional football, selecting players involves evaluating multiple criteria to ensure optimal team performance. This paper introduces a novel approach for optimizing player selection by combining the Random Forest algorithm for criterion weighting with the multi-criteria decision-making method...

Every year Saudi Arabia receives millions of Muslims which come from all over the world to perform religious rituals of Hajj (Pilgrimage) during Hajj seasons. Therefore, planning an efficient transportation system is important to facilitate pilgrims / bus movement between holly cities (Makka, Mina, Mozdalifah...

Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) is an effective method for early ischemic stroke detection, often identifying strokes within the first few minutes of onset. Additionally, it enables the quantification of lesion volume, which is a critical factor in determining whether to proceed...

This paper presents a novel approach for optimizing the hyperparameters of Artificial Neural Networks (ANNs) using metaheuristic algorithms to solve the inverse kinematics problem for a 3-DoF rehabilitation exoskeleton robot. The exoskeleton aims to assist in rehabilitation by enabling accurate control...

Predicting Gestational Diabetes Mellitus (GDM) is crucial for pregnant women to enable regular monitoring of their blood sugar levels and adherence to a healthy diet. Early intervention can significantly lower the risk of developing this condition. To assess this risk, Machine Learning (ML) and Deep...

During emergencies and pandemics, such as COVID-19 or Mpox, the massive demand for critical resources, including hospital beds, has significantly challenged healthcare systems. Reducing the pressure on these systems is crucial and requires an efficient strategy for patient allocation. This paper proposes...

Autism Spectrum Disorder (ASD), as a developmental disorder, causes difficulties in social interaction, communication, sharing emotions, making their education and daily life complicated. We aim to help these children and their parents to reduce cognitive impairment, maximize independence and improve...

This research focuses on task allocation in a diverse workforce to address the challenges modern companies face in the competitive business environment within the context of Industry 5.0. It examines the potential of Simulation-Based Optimization (SBO) in resolving these issues. Initially, a mathematical...

This paper addresses the online surgery planning and scheduling problem for operating rooms and recovery beds. We aim to minimize the makespan by dynamically assigning surgery dates, operating rooms, and recovery beds. Our integrated framework uses a Mixed-Integer Linear Program (MILP)...

Efficient and timely distribution of blood is crucial for ensuring that patients receive the necessary medical treatments within critical timeframes. Delays in blood delivery can significantly impact patient outcomes, as prompt availability of blood products is essential for effective medical care. This...

Effective supply chain management (SCM) minimizes expenses while maintaining material flow balance. This paper highlights the lack of Working Capital Requirement (WCR), a crucial metric for evaluating organizational liquidity and financial stability, in Supply Chain Optimization despite research indicating...

One of the major challenges to the adoption of ubiquitous learning systems is the complexity and time involved in recommending the appropriate learning strategy. Within this context, this paper shows how a fuzzy ontology-based algorithm can recommend an appropriate learning strategy in a ubiquitous learning...

In online learning, the accurate prediction of student performance is essential for timely interventions and personalized learning experiences. This work leverages the Open University Learning Analytics Dataset (OULAD) to evaluate the effectiveness of various machine learning (ML) and deep learning (DL)...

This study examines the teaching of software design and development using an active learning approach centered around a practical IT project. Students were organized into groups and tasked with developing a functional software product based on specific requirements. Throughout the project, teams encountered...