THE FUTURE OF MEDICINE, healthcare innovation through precision medicine: policy case study of Qatar by M. Walid Qoronfleh (14153088)

“…Consequently, the big data revolution has provided an opportunity to apply artificial intelligence and machine learning algorithms to mine such a vast data set. …”

Artificial Intelligence for Skin Cancer Detection: Scoping Review by Abdulrahman Takiddin (14153181)

“…Hence, to aid in diagnosing skin cancer, artificial intelligence (AI) tools are being used, including shallow and deep machine learning–based methodologies that are trained to detect and classify skin cancer using computer algorithms and deep neural networks.…”

An Improved Genghis Khan Optimizer based on Enhanced Solution Quality Strategy for Global Optimization and Feature Selection Problems by Abdel-Salam, Mahmoud

“…The primary goals of feature selection are to decrease the number of dimensions and enhance classification accuracy in many domains, such as text classification, large-scale data analysis, and pattern recognition. Several metaheuristics, such as the Genghis Khan Shark Optimizer Algorithm (GKSO), can assist in optimizing the FS issue. …”
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Plant disease detection using drones in precision agriculture by Ruben Chin (17725986)

“…The machine learning algorithm applied most is convolutional neural network (CNN). …”

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

“…The type of algorithm employed to predict drug release from liposomes plays an important role in affecting the accuracy. …”
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Image-CNN Based Process Control of Profile by Zeinab, Zeinab Jihad

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Decision-level Gait Fusion for Human Identification at a Distance by Al-Tayyan, Amer

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Deep Neural Networks for Electromagnetic Inverse Scattering Problems in Microwave Imaging by Maricar, Mohammed Farook

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Extreme Early Image Recognition Using Event-Based Vision by Abubakar Abubakar (18278998)

“…<p dir="ltr">While deep learning algorithms have advanced to a great extent, they are all designed for frame-based imagers that capture images at a high frame rate, which leads to a high storage requirement, heavy computations, and very high power consumption. …”

Enhancing building sustainability: A Digital Twin approach to energy efficiency and occupancy monitoring by Aya Nabil Sayed (17317006)

“…The DT technology enabled the creation of accurate virtual representations of users' physical environment, facilitating the optimization of energy-intensive devices and systems. Our data-driven occupancy detection approach utilized Machine Learning (ML) algorithms to intelligently determine room occupancy, allowing for precise energy management based on real-time usage patterns. …”

EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach by Muhammad Adeel Asghar (6724982)

“…The BoDF model achieves 93.8% accuracy in the SEED data set and 77.4% accuracy in the DEAP data set, which is more accurate compared to other state-of-the-art methods of human emotion recognition.…”

Decision-level fusion for single-view gait recognition with various carrying and clothing conditions by Al-Tayyan, Amer

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Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier by Syed Ali Jafar Zaidi (19563178)

“…<div><p>Machine learning (ML)-based prediction is considered an important technique for improving decision making during the planning process. …”

Automated systems for diagnosis of dysgraphia in children: a survey and novel framework by Jayakanth Kunhoth (14158908)

“…This work discusses the data collection method, important handwriting features, and machine learning algorithms employed in the literature for the diagnosis of dysgraphia. …”

Diagnostic test accuracy of AI-assisted mammography for breast imaging: a narrative review by Daksh Dave (17949239)

Prediction of Multiple Clinical Complications in Cancer Patients to Ensure Hospital Preparedness and Improved Cancer Care by Regina Padmanabhan (14231606)

A novel hybrid methodology for fault diagnosis of wind energy conversion systems by Khaled Dhibi (16891524)

Ensemble Deep Random Vector Functional Link Neural Network for Regression by Minghui Hu (2457952)

“…<p dir="ltr">Inspired by the ensemble strategy of machine learning, deep random vector functional link (dRVFL), and ensemble dRVFL (edRVFL) has shown state-of-the-art results on different datasets. …”

An Effective Fault Diagnosis Technique for Wind Energy Conversion Systems Based on an Improved Particle Swarm Optimization by Majdi Mansouri (16869885)

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

“…</p><h3>Objectives</h3><p dir="ltr">This study aims to evaluate and compare the predictive accuracy of AI algorithms in predicting the mode of delivery (vaginal or cesarean) using routinely collected antepartum data from electronic health records (EHRs). …”