Applications of artificial intelligence in ultrasound imaging for carpal-tunnel syndrome diagnosis: a scoping review by Yosra Magdi Mekki (21673721)

“…All eighteen studies shared the common objective of improving CTS diagnosis and/or initial assessment using AI, with shared aims ranging from median nerve segmentation (<i>n</i> = 12) to automated diagnosis (<i>n</i> = 9) and severity classification (<i>n</i> = 2). The majority of studies utilized deep learning approaches, particularly CNNs (<i>n</i> = 15), and some focused on radiomics features (<i>n</i> = 5) and traditional machine learning techniques.…”

Seven novel glucose-6-phosphate dehydrogenase (G6PD) deficiency variants identified in the Qatari population by Shaza Malik (18456735)

“…Furthermore, we have identified seven novel G6PD variants, all of which were confirmed as G6PD-causing variants and classified as class III variants based on the World Health Organization’s classification scheme.</p><h3>Conclusions</h3><p dir="ltr">This is the first study investigating the molecular basis of G6PDD in Qatar, and it provides novel insights about G6PDD pathogenesis and highlights the importance of studying such understudied population.…”

Hydrogeochemical characterization and quality evaluation of groundwater suitability for domestic and agricultural uses in the state of Qatar by Ayesha Y. Ahmad (14152779)

“…A positive loading of Mg, Th, Sr, Ca, TDS, SO4, Li, Cl, F, Br, Cd, K, Ba, and Na has been shown by the PC1; representing the factors which are contributing to the high salinity of the GW due to the salt water intrusion and the mineralization of rocks and soil which is supported by the water type classification and saturation indices. The PC2 showed a negative loading of U, Al, Se, Mo, Mg, and temperature, which could be associated with a localized sedimentary depositional or hydrogeochemical environment. …”

An End-to-End Deep Learning Framework for Real-Time Denoising of Heart Sounds for Cardiac Disease Detection in Unseen Noise by Shams Nafisa Ali (17949191)

“…In addition, the proposed denoising method model improves classification accuracy by 38.93% in the noisy portion of the PASCAL heart sound dataset. …”

Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms by Usman Ali (6586886)

“…<p dir="ltr">Land use and land cover (LULC) classification maps help understand the state and trends of agricultural production and provide insights for applications in environmental monitoring. …”

Artificial intelligence models for predicting the mode of delivery in maternal care by Rawan AlSaad (14159019)

“…A comprehensive feature importance analysis was conducted on the trained models to identify the key predictors influencing the mode of delivery classification. </p><h3>Results</h3><p dir="ltr">All five models demonstrated excellent predictive performance, with AdaBoost and XGBoost achieving nearly identical top scores across most metrics: ROC-AUC (90 %), accuracy (89 %), PR-AUC (83 %), and F1 score (88 %) Feature importance analysis highlighted the most predictive factors for mode of delivery. …”

Genome‐wide DNA methylation analysis of colorectal adenomas with and without recurrence reveals an association between cytosine‐phosphate‐guanine methylation and histological subty... by David Fiedler (2672563)

“…In conclusion, our methylation data could assist in establishing a more robust and reproducible histological adenoma classification, which is a prerequisite for improving surveillance guidelines.…”

Ancestry-associated transcriptomic profiles of breast cancer in patients of African, Arab, and European ancestry by Jessica Roelands (7516439)

“…We applied a unique approach that combines the use of curated survival data from The Cancer Genome Atlas (TCGA) Pan-Cancer clinical data resource, improved single-nucleotide polymorphism-based inferred ancestry assignment, and a novel breast cancer subtype classification to interrogate the TCGA and a local Arab breast cancer dataset. …”

Real-Time Green View Index Assessment: AI-Driven Analysis of Urban Vegetation Using Dashcam Videos by Karam Masad (22827149)

“…., trees), and “terrain,” which represents horizontal greenery (e.g., grass). This classification allows us to prioritize vertical greenery, by giving it greater weighting, which generally offers greater ecological and aesthetic benefits in urban environments. …”

A sentiment reporting framework for major city events: Case study on the China-United States trade war by AlKhatib, Manarc

“…The results show that the convolutional neural network (CNN) classifier used for sentiment analysis yielded a classification accuracy of 86% when differentiating between four sentiment categories: Support, strong support, dissent, and strong dissent. …”
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القراءات في الحجاز تأثّرًا وتأثيرًا من أول عصر التلقّي إلى نهاية الطبقة الثانية عشرة by Halabi, Omaimah Abdulrahman

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A comparative study of the evolution of vulnerabilities in IT systems and its relation to the new concept of cloud computing by Kouatli, Issam

“…Originality/value – A new comparative study and new classification of vulnerabilities demonstrated with risk analysis using simple scoring technique.…”
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Inflammatory biomarkers as predictors for unlocking antidepressant efficacy: Assessing predictive value and risk stratification in major depressive disorder in a prospective longit... by Nervana Elbakary (21480140)

“…Folate levels and PLR were identified by the machine learning model as top predictors, suggesting potential utility as biomarkers for response classification. Our study identified predictors of improvement in suicidal ideation, including hematological markers (lower RBC, higher eosinophils, lower monocytes), younger age, female sex, medical comorbidities, and longer assessment intervals. …”

PFDI: a precise fruit disease identification model based on context data fusion with faster-CNN in edge computing environment by Poonam Dhiman (12889038)

“…Many researchers have suggested deep and machine learning-based fruit disease detection and classification models. This research presents a precise fruit disease identification model based on context data fusion with Faster-CNN in an edge computing environment. …”

Machine Learning-Based Management of Electric Vehicles Charging: Towards Highly-Dispersed Fast Chargers by Mostafa Shibl (18810412)

“…These approaches are chosen as they are classifiers known to have the leading results for multiclass classification problems. The results found shed insight on the importance of the techniques used and their high potential in providing a reliable solution for the coordinated charging of EVs, thus improving the performance of the power grid, and reducing power losses and voltage fluctuations. …”

Development of an innovative clinical pharmacy service in a urology surgical unit: a new initiative from Qatar by Lina Naseralallah (14146465)

“…Data related to clinical pharmacist interventions and associated rationale were classified according to the nature of the intervention using an adapted classification system. The assessment of the severity followed the National Patient Safety Agency (NPSA) Risk Matrix. …”

Seasonal variations in feed-water chemistry and fouling dynamics of reverse-osmosis systems: A global climate lens by Nasser Zareei (22921226)

“…This review synthesizes RO studies published from 2015 to 2025 across hot-desert, Mediterranean, temperate, and tropical climate zones using Köppen-Geiger climate classification as an organizing framework, the first systematic climate-resolved synthesis of seasonal fouling mechanisms and adaptive responses. …”

An Ensemble Deep Learning Approach for Accurate Urinary Sediment Detection Using YOLOv9e and KD-YOLOX-ViT by Mansura Naznine (21399893)

“…This ensemble framework combines the strengths of YOLOv9e and KD-YOLOX-ViT models to automate the detection and classification of seven distinct urine sediment particles, effectively addressing challenges related to class imbalance, image resolution, and domain adaptation. …”

Validation of the emergency surgery score’s predictive accuracy for postoperative outcomes and ICU admissions in MENA vs. non-MENA emergency surgery patients by Mohamed Said Ghali (16810713)

“…ESS scores were calculated for each patient, and its predictive accuracy was compared with the American Society of Anesthesiologists (ASA) classification using c-statistic methodology. We also compared postoperative outcomes between MENA and non-MENA cohorts to assess potential regional variations in ESS performance.…”

Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data by Arfan Ahmed (17541309)

“…One of the key aspects of WDs with machine learning (ML) algorithms is to find specific data signatures, called Digital biomarkers, that can be used in classification or gaging the extent of the underlying condition. …”