83 citations · 162 across the 24 of their papers we have counts for
25 papers
MentalMARBERT: Domain-Adaptive Pre-training and Two-Stage Fine-Tuning for Arabic Mental Health Disorders Detection
Fatimah Almalki, Areej Alhothali, Lulwah Alharigy +1
Detecting mental health disorders from Arabic social media text remains challenging due to dialectal variation, informal language, limited high-quality annotated resources, and sev…
A Dual Cross-Attention Graph Learning Framework For Multimodal MRI-Based Major Depressive Disorder Detection
Nojod M. Alotaibi, Areej M. Alhothali
Major depressive disorder (MDD) is a prevalent mental disorder associated with complex neurobiological changes that cannot be fully captured using a single imaging modality. The us…
Placenta Accreta Spectrum Detection using Multimodal Deep Learning
Sumaiya Ali, Areej Alhothali, Sameera Albasri +3
Placenta Accreta Spectrum (PAS) is a life-threatening obstetric complication involving abnormal placental invasion into the uterine wall. Early and accurate prenatal diagnosis is e…
Placenta Accreta Spectrum Detection Using an MRI-based Hybrid CNN-Transformer Model
Sumaiya Ali, Areej Alhothali, Ohoud Alzamzami +3
Placenta Accreta Spectrum (PAS) is a serious obstetric condition that can be challenging to diagnose with Magnetic Resonance Imaging (MRI) due to variability in radiologists' inter…
ArbESC+: Arabic Enhanced Edit Selection System Combination for Grammatical Error Correction Resolving conflict and improving system combination in Arabic GEC
Ahlam Alrehili, Areej Alhothali
Grammatical Error Correction (GEC) is an important aspect of natural language processing. Arabic has a complicated morphological and syntactic structure, posing a greater challenge…
Domain-Adaptive Pre-Training for Arabic Aspect-Based Sentiment Analysis: A Comparative Study of Domain Adaptation and Fine-Tuning Strategies
Salha Alyami, Amani Jamal, Areej Alhothali
Aspect-based sentiment analysis (ABSA) in natural language processing enables organizations to understand customer opinions on specific product aspects. While deep learning models…
Continuous Saudi Sign Language Recognition: A Vision Transformer Approach
Soukeina Elhassen, Lama Al Khuzayem, Areej Alhothali +2
Sign language (SL) is an essential communication form for hearing-impaired and deaf people, enabling engagement within the broader society. Despite its significance, limited public…
3DViT-GAT: A Unified Atlas-Based 3D Vision Transformer and Graph Learning Framework for Major Depressive Disorder Detection Using Structural MRI Data
Nojod M. Alotaibi, Areej M. Alhothali, Manar S. Ali
Major depressive disorder (MDD) is a prevalent mental health condition that negatively impacts both individual well-being and global public health. Automated detection of MDD using…
TransGAT: Transformer-Based Graph Neural Networks for Multi-Dimensional Automated Essay Scoring
Hind Aljuaid, Areej Alhothali, Ohoud Al-Zamzami +1
Essay writing is a critical component of student assessment, yet manual scoring is labor-intensive and inconsistent. Automated Essay Scoring (AES) offers a promising alternative, b…
Evaluating Multimodal Large Language Models on Educational Textbook Question Answering
Hessa A. Alawwad, Anas Zafar, Areej Alhothali +3
Multimodal large language models (MLLMs) have shown success in vision-language tasks, but their ability to reason over complex educational materials remains largely untested. This…
Beyond Retrieval: Joint Supervision and Multimodal Document Ranking for Textbook Question Answering
Hessa Alawwad, Usman Naseem, Areej Alhothali +2
Textbook question answering (TQA) is a complex task, requiring the interpretation of complex multimodal context. Although recent advances have improved overall performance, they of…
Towards the Development of Balanced Synthetic Data for Correcting Grammatical Errors in Arabic: An Approach Based on Error Tagging Model and Synthetic Data Generating Model
Ahlam Alrehili, Areej Alhothali
Synthetic data generation is widely recognized as a way to enhance the quality of neural grammatical error correction (GEC) systems. However, current approaches often lack diversit…
Multi-atlas Ensemble Graph Neural Network Model For Major Depressive Disorder Detection Using Functional MRI Data
Nojod M. Alotaibi, Areej M. Alhothali, Manar S. Ali
Major depressive disorder (MDD) is one of the most common mental disorders, with significant impacts on many daily activities and quality of life. It stands as one of the most comm…
Tibyan Corpus: Balanced and Comprehensive Error Coverage Corpus Using ChatGPT for Arabic Grammatical Error Correction
Ahlam Alrehili, Areej Alhothali
Natural language processing (NLP) utilizes text data augmentation to overcome sample size constraints. Increasing the sample size is a natural and widely used strategy for alleviat…
Enhancing textual textbook question answering with large language models and retrieval augmented generation
Hessa Abdulrahman Alawwad, Areej Alhothali, Usman Naseem +2
Textbook question answering (TQA) is a challenging task in artificial intelligence due to the complex nature of context needed to answer complex questions. Although previous resear…
Arabic Tweet Act: A Weighted Ensemble Pre-Trained Transformer Model for Classifying Arabic Speech Acts on Twitter
Khadejaa Alshehri, Areej Alhothali, Nahed Alowidi
Speech acts are a speakers actions when performing an utterance within a conversation, such as asking, recommending, greeting, or thanking someone, expressing a thought, or making…
Detecting Suicidality in Arabic Tweets Using Machine Learning and Deep Learning Techniques
Asma Abdulsalam, Areej Alhothali, Saleh Al-Ghamdi
Social media platforms have revolutionized traditional communication techniques by enabling people globally to connect instantaneously, openly, and frequently. People use social me…
ALJP: An Arabic Legal Judgment Prediction in Personal Status Cases Using Machine Learning Models
Salwa Abbara, Mona Hafez, Aya Kazzaz +2
Legal Judgment Prediction (LJP) aims to predict judgment outcomes based on case description. Several researchers have developed techniques to assist potential clients by predicting…
Hybrid Classifiers for Spatio-temporal Real-time Abnormal Behaviors Detection, Tracking, and Recognition in Massive Hajj Crowds
Tarik Alafif, Anas Hadi, Manal Allahyani +4
Individual abnormal behaviors vary depending on crowd sizes, contexts, and scenes. Challenges such as partial occlusions, blurring, large-number abnormal behavior, and camera viewi…
Suicidal Ideation Detection on Social Media: A Review of Machine Learning Methods
Asma Abdulsalam, Areej Alhothali
Social media platforms have transformed traditional communication methods by allowing users worldwide to communicate instantly, openly, and frequently. People use social media to e…
Detection of Hate Speech using BERT and Hate Speech Word Embedding with Deep Model
Hind Saleh, Areej Alhothali, Kawthar Moria
The enormous amount of data being generated on the web and social media has increased the demand for detecting online hate speech. Detecting hate speech will reduce their negative…
Pre-trained Transformer-Based Approach for Arabic Question Answering : A Comparative Study
Kholoud Alsubhi, Amani Jamal, Areej Alhothali
Question answering(QA) is one of the most challenging yet widely investigated problems in Natural Language Processing (NLP). Question-answering (QA) systems try to produce answers…
Detecting White Supremacist Hate Speech using Domain Specific Word Embedding with Deep Learning and BERT
Hind Saleh Alatawi, Areej Maatog Alhothali, Kawthar Mustafa Moria
White supremacists embrace a radical ideology that considers white people superior to people of other races. The critical influence of these groups is no longer limited to social m…
Semi-Supervised Affective Meaning Lexicon Expansion Using Semantic and Distributed Word Representations
Areej Alhothali, Jesse Hoey
In this paper, we propose an extension to graph-based sentiment lexicon induction methods by incorporating distributed and semantic word representations in building the similarity…