Antibiotic Resistance, Virulence Factors and Whole-Genome Characterization of Enterobacter spp. and Klebsiella aerogenes isolated from hospitals in Lebanon by Ghafari, Patricia

“…Identification and classification of 21 Enterobacter species and three K. aerogenes, was performed through hsp60 genotyping and 16S rRNA gene sequencing and confirmed by whole-genome average nucleotide identity (wgANI). …”
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Evaluation and management of complications from synthetic mesh after pelvic reconstructive surgery by Abbott, Sara

“…Demographic, clinical, and surgical data were abstracted from the medical record, and complications were classified according to the Expanded Accordion Severity Classification. Results Three hundred forty-seven patients sought management of synthetic mesh-related complications over the study period. …”
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On-demand mobile sensing framework for traffic monitoring. (c2017) by Abdul Rahman, Sawsan

“…Moreover, we extend our approach by elaborating (1) cellular networks based model for selecting suitable set of mobile devices acting as data collectors and (2) inference rules based on deductive logic for traffic status classification inferred from both density and mean speed. …”
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A novel few shot learning derived architecture for long-term HbA1c prediction by Marwa Qaraqe (10135172)

“…Finally, a K-nearest neighbor (KNN) model with majority voting is implemented for the final classification task. The proposed FSL-derived algorithm provides a prediction accuracy of 93.2%.…”

RL-PDNN: Reinforcement Learning for Privacy-Aware Distributed Neural Networks in IoT Systems by Emna Baccour (16896366)

“…Particularly, in Internet of Things (IoT) systems, the data acquired by pervasive devices is sent to the computing servers for classification. However, this approach might not be always possible because of the limited bandwidth and the privacy issues. …”

The demographics of Tolosa-Hunt syndrome in Qatar by Fateen Ata (12217764)

“…The International Classification of Headache Disorders (ICHD)- 3 diagnostic criteria aids in its diagnosis. …”

Decomposition-based wind power forecasting models and their boundary issue: An in-depth review and comprehensive discussion on potential solutions by Yinsong Chen (16685508)

“…We also evaluate the strengths and limitations of the existing boundary issue solutions and discuss their applicability to different classification of decomposition-based models for wind power forecasting. …”

Zero-shot motor health monitoring by blind domain transition by Serkan Kiranyaz (3762058)

“…Even with the recent deep learning (DL) methodologies trained on the labeled data from the same machine, the classification accuracy significantly deteriorates when one or few conditions are altered, e.g., a different speed or load, or for different fault types/severities with sensors placed in different locations. …”

Interval-Valued Reduced Ensemble Learning Based Fault Detection and Diagnosis Techniques for Uncertain Grid-Connected PV Systems by Khaled Dhibi (16891524)

“…The IKPCA-EL techniques are addressed so that the features extraction and selection phases are performed using the IKPCA models and the sensitive and significant interval-valued characteristics are transmitted to the EL model for classification purposes. Finally, the number of observations in the training data set is reduced using Hierarchical K-means techniques in order to overcome the problem of computation time and storage cost. …”

Precision nutrition: A systematic literature review by Daniel Kirk (17302798)

“…Four machine learning tasks are seen in the form of regression, classification, recommendation and clustering, with most of these utilizing a supervised approach. …”

Investigating the structural impacts of a novel missense variant identified with whole exome sequencing in an Egyptian patient with propionic acidemia by Ali Zaki Ibrahim (17092957)

“…The current study demonstrates that the combination of whole-exome sequencing (WES) and computational analysis are potent tools for validation of diagnosis and classification of disease-causing variants.</p><h2>Other Information</h2><p dir="ltr">Published in: Molecular Genetics and Metabolism Reports<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.ymgmr.2020.100645" target="_blank">https://dx.doi.org/10.1016/j.ymgmr.2020.100645</a></p>…”

Decoding silent speech: a machine learning perspective on data, methods, and frameworks by Adiba Tabassum Chowdhury (19444792)

“…The field's proposed procedures are examined, with an emphasis on sophisticated feature extraction and classification methods. Modern SSR techniques are compared in terms of performance, highlighting the advantages and disadvantages of different models. …”

An Intelligent and Low-Cost Eye-Tracking System for Motorized Wheelchair Control by Mahmoud Dahmani (18810247)

“…CNN exhibited the best performance (i.e., 99.3% classification accuracy), and thus it was the model of choice for the gaze estimator, which commands the wheelchair motion. …”

Why does the adverse effect of inappropriate MRI for LBP vary by geographic location? An exploratory analysis by Mujahed Shraim (14153145)

“…LBP cases with at least 1 day of work disability were identified by reviewing indemnity service records and medical bills using a comprehensive list of codes from the International Classification of Diseases, Ninth Edition (ICD-9) indicating LBP or nonspecific back pain, excluding medically complicated cases.…”

Epidemiology of proximal femur fractures in the young population of Qatar by Ashraf T. Hantouly (14150319)

“…All adults (18–60 years) with proximal femur fracture (femur head, femur neck, intertrochanteric and subtrochanteric fractures) were included with no restriction to the AO/OTA classification or fractures subtypes. Excluded cases were pathological fractures, cases with insufficient documentation or no radiographs.…”

PAST-AI: Physical-Layer Authentication of Satellite Transmitters via Deep Learning by Gabriele Oligeri (14151426)

“…<p dir="ltr">Physical-layer security is regaining traction in the research community, due to the performance boost introduced by deep learning classification algorithms. This is particularly true for sender authentication in wireless communications via radio fingerprinting. …”

Hybrid Model for Detection of Cervical Cancer Using Causal Analysis and Machine Learning Techniques by Umesh Kumar Lilhore (17727684)

“…It is improved from of random forest method and mainly discovers feature subsets from the data source that are significant to assigned classification activity. The proposed model’s primary aim is to determine the importance of cervical cancer screening factors for classifying high-risk patients depending on the findings. …”

IP SafeGuard–An AI-Driven Malicious IP Detection Framework by Abdullah Al Siam (22502732)

“…It leverages an XGBoost-based classification model to achieve high accuracy and low false-positive rates, even in skewed datasets. …”

Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by Marwan Dhuheir (19170898)

“…A key requirement in these applications is minimizing the latency of data processing, particularly for time-sensitive tasks like image classification of IIoT device data. Due to resource limitations, UAVs often rely on online task offloading to remote machines, but this can be inefficient due to unstable connections, constrained resources, and high latency. …”

Virtual Inertia Support in Power Systems for High Penetration of Renewables—Overview of Categorization, Comparison, and Evaluation of Control Techniques by Naruttam Kumar Roy (16904544)

“…Furthermore, to emphasize the most promising ones, the VIC approaches are classified as intelligent, adaptive, derivative, coordinated control, and other VIC techniques. The classification approach is followed by the system configuration and the mode of operation of each control scheme. …”