Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test حسب Hasan T. Abbas (8115014)

"…Data generated from an oral glucose tolerance test (OGTT) was used to develop a predictive model based on the support vector machine (SVM). We trained and validated the models using the OGTT and demographic data of 1,492 healthy individuals collected during the San Antonio Heart Study. …"

Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications حسب Estahbanati, Shahabeddin Vamegh

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Automated liver tissues delineation techniques: A systematic survey on machine learning current trends and future orientations حسب Ayman Al-Kababji (16870080)

"…Hence, in this paper, we survey the key studies that are published between 2014 and 2022, showcasing the different machine learning algorithms researchers have used to segment the liver, hepatic tumors, and hepatic-vasculature structures. …"

An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study حسب Ayman Hassan (14426412)

"…We aimed to develop an app using a comprehensive geomapping navigation and estimation system based on machine learning algorithms. This app uses key stroke-related timelines including the last time the patient was known to be well, patient location, treatment options, and imaging availability at different health care facilities.…"

The Detection of Dysarthria Severity Levels Using AI Models: A Review حسب Afnan Al-Ali (16888695)

Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model حسب Ramesh Sundar (19326046)

Predicting Calcein Release from Ultrasound-Targeted Liposomes: A Comparative Analysis of Random Forest and Support Vector Machine حسب Shomope, Ibrahim

"…In this regard, Random Forest (RF) and Support Vector Machine (SVM) are two ML algorithms that have been extensively applied in various biomedical and drug delivery contexts. …"
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Towards secure private and trustworthy human-centric embedded machine learning: An emotion-aware facial recognition case study حسب Muhammad Atif Butt (10849980)

"…Since the success of AI is to be measured ultimately in terms of how it benefits human beings, and that the data driving the deep learning-based edge AI algorithms are intricately and intimately tied to humans, it is important to look at these AI technologies through a human-centric lens. …"

Inertial Navigation system of In-pipe Inspection Robot حسب Al-Masri, Wasim

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Predicting insulin dosage for diabetic patients to reach optimal glucose levels. (c2012) حسب Bitar, Mandy

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Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches حسب Natasha Akram (20749538)

"…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …"

A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security حسب S. Shitharth (12017480)

"…Moreover, the Reconciliate Multi-Agent Markov Learning (RMML) based classification algorithm is used to predict the intrusion with its appropriate classes. …"

DNA Base-Calling Techniques حسب Odeh, Fadi

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Arabic Text Classification Using Modified Artificial Bee Colony Algorithm for Sentiment Analysis: The Case of Jordanian Dialect حسب Habeeb, Abdallah

"…The second phase, modified the Artificial Bee Colony (ABC) Algorithm, with Upper Confidence Bound (UCB) Algorithm, to promote the exploitation ability for the minimum dimension, to get the minimum number of the optimal feature, then using forward feature selection strategy by four classifiers of machine learning algorithms: (K-Nearest Neighbors (KNN), Support vector machines (SVM), Naïve-Bayes (NB), and Polynomial Neural Networks (PNN). …"
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Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE حسب Ben Romdhane, Haifa

"…The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …"
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Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE حسب Ben-Romdhane, Haïfa

"…The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …"
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DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins حسب Samir Brahim, Belhaouari

"…ResultMost traditional machine learning algorithms achieved distinction accuracies of over 99 percent, whereas DeepRaman demonstrated an exceptional accuracy of 100 percent. …"
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Wearable wrist to finger photoplethysmogram translation through restoration using super operational neural networks based 1D-CycleGAN for enhancing cardiovascular monitoring حسب Sakib Mahmud (15302404)

"…Current signal processing techniques, and even state-of-the-art machine learning algorithms, frequently struggle to effectively restore the inherent bodily signals amidst the array of randomly generated distortions. …"

An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting حسب Mohamed Massaoudi (16888710)

Global smart cities classification using a machine learning approach to evaluating livability, technology, and sustainability performance across key urban indices حسب Aya Hasan Alkhereibi (17151070)

"…This study aims to classify the highest 50 global smart cities based on key livability and technology indices, using advanced <u>machine learning</u> (ML) models to assess city performance comprehensively. …"