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)

A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI حسب Oishi Jyoti (21593819)

"…<p dir="ltr">Autism Spectrum Disorder (ASD) is a genetic and neurological condition that leads to difficulties in communication and social interaction. The global concern associated with ASD diagnosis is increasing at a rapid rate due to its significant impact on quality of life. …"

Impacts of climate change on the global spread and habitat suitability of <i>Coxiella burnetii</i>: Future projections and public health implications حسب Abdallah Falah Mohammad Aldwekat (22457821)

"…</p><h3>Materials and methods</h3><p dir="ltr">An ensemble<u> species distribution modelling </u>approach, integrating regression-based and machine-learning algorithms (GLM, GBM, RF, MaxEnt), was used to project habitat suitability (Current time and by 2050, 2070, and 2090). …"

Intelligent Bilateral Client Selection in Federated Learning Using Game Theory حسب Wehbi, Osama

"…Based on our simulation findings, our strategy surpasses the VanillaF selection approach in terms of maximizing both the revenues of the client devices and accuracy of the global federated learning model.…"
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Exploratory risk prediction of type II diabetes with isolation forests and novel biomarkers حسب Yousef, Hibba

"…Type II diabetes mellitus (T2DM) is a rising global health burden due to its rapidly increasing prevalence worldwide, and can result in serious complications. …"
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Exploring new horizons in neuroscience disease detection through innovative visual signal analysis حسب Nisreen Said Amer (17984077)

"…To address this, our study focuses on visualizing complex EEG signals in a format easily understandable by medical professionals and deep learning algorithms. We propose a novel time–frequency (TF) transform called the Forward–Backward Fourier transform (FBFT) and utilize convolutional neural networks (CNNs) to extract meaningful features from TF images and classify brain disorders. …"