Fast and Efficient Image Generation Using Variational Autoencoders and K-Nearest Neighbor OveRsampling Approach by Ashhadul Islam (16869981)

“…We fine-tune several pre-trained networks on a separate set of real and fake face images to test images generated by our method against images generated by conventional Deep Convolutional GANs (DCGANs). …”

Real-time AI-based inference of people gender and age in highly crowded environments by Jasseur Abidi (17870426)

“…The objective of this paper is to address the challenges of gender and age identification in very crowded/noisy environments where faces are unclear and/or people are moving in relatively random directions. …”

Bias-aware face mask detection dataset by Alperen Kantarcı (20151456)

“…Early attempts to collect face mask datasets did not account for potential race, gender, and age biases. …”

MEDIC: a multi-task learning dataset for disaster image classification by Firoj Alam (14158866)

“…<p>Recent research in disaster informatics demonstrates a practical and important use case of artificial intelligence to save human lives and suffering during natural disasters based on social media contents (text and images). …”

Machine learning based model for the early detection of Gestational Diabetes Mellitus by Hesham Zaky (22392529)

“…</p><h3>Conclusion</h3><p dir="ltr">We believe our findings will complement the current clinical practice of GDM diagnosis at an early stage of pregnancy, leading toward minimizing its burden on the healthcare system.Source code is available in GitHub at: https://github.com/H-Zaky/GD.git</p><h2>Other Information</h2><p dir="ltr">Published in: BMC Medical Informatics and Decision Making<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1186/s12911-025-02947-3" target="_blank">https://dx.doi.org/10.1186/s12911-025-02947-3</a></p>…”

Kinship recognition from faces using deep learning with imbalanced data by Hadid, Abdenour

“…In this work, We propose a novel pattern analysis technique for kinship verification based on a new deep learning-based approach. More specifically, given a pair of face images, we first use Resnet50 to extract deep features from each image. …”
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MSLP: mRNA subcellular localization predictor based on machine learning techniques by Saleh Musleh (15279190)

“…We propose a novel combination of four types of features representing k-mer, pseudo k-tuple nucleotide composition (PseKNC), physicochemical properties of nucleotides, and 3D representation of sequences based on Z-curve transformation to feed into machine learning algorithm to predict the subcellular localization of mRNAs.…”

Machine learning based personalized drug response prediction for lung cancer patients by Rizwan Qureshi (15279193)

“…Targeted tyrosine kinase inhibitors (TKIs) have been developed against EGFR and show encouraging results for survival rate and quality of life. …”

MSEUnet: Refined Intima-media segmentation of the carotid artery based on a multi-scale approach using patch-wise dice loss by Najmath Ottakath (17430912)

“…The source code for the functions discussed in this paper will be available at https://github.com/Vlabgit/MSEUnet.git.…”

A Comprehensive Overview of the COVID-19 Literature: Machine Learning–Based Bibliometric Analysis by Alaa Abd-Alrazaq (17430900)

“…We have made our software accessible to the community via GitHub.…”

COVID-19Base v3: Update of the knowledgebase for drugs and biomedical entities linked to COVID-19 by Syed Abdullah Basit (18021787)

“…Eight different topic-specific dictionaries, i.e., gene, miRNA, lncRNA, PDB entries, disease, alternative medicines registered under clinical trials, drugs, and the side effects of drugs, were used to build this knowledgebase. We have introduced a BLSTM-based deep-learning model to predict the drug-disease associations that outperforms the existing model for the same purpose proposed in the earlier version of COVID-19Base. …”

A Novel Bayesian Outlier Score Based on the Negative Binomial Distribution for Detecting Aberrantly Expressed Genes in RNA-Seq Gene Expression Count Data by Edin Salkovic (16891479)

“…The code for our model is available at <a href="https://github.com/esalkovic/outpyrx" rel="nofollow">https://github.com/esalkovic/outpyrx</a>.…”

LNCRI: Long Non-Coding RNA Identifier in Multiple Species by Saleh Musleh (15279190)

“…To overcome these challenges we developed LNCRI (Long Non-Coding RNA Identifier), a novel machine learning (ML)-based tool for the identification of lncRNA transcripts. …”

Ultraliser: a framework for creating multiscale, high-fidelity and geometrically realistic 3D models for <i>in silico</i> neuroscience by Marwan Abdellah (4435360)

“…The framework represents a major leap forward in simulation-based neuroscience, making it possible to employ high-resolution 3D structural models for quantification of surface areas and volumes, which are of the utmost importance for cellular and system simulations. …”

Oversampling techniques for imbalanced data in regression by Samir Brahim Belhaouari (9427347)

“…This success rate is determined by the frequency of instances where models performed better when augmented data was used compared to instances with no augmentation. …”

Variable Selection in Data Analysis: A Synthetic Data Toolkit by Mitra, Rohan

“…Additionally, eight FSAs are evaluated on these datasets based on their relevance and novelty. The paper first introduces the datasets and then provides a comprehensive experimental analysis of the performance of the selected FSAs on these datasets including testing the FSAs’ resilience on two types of induced data noise. …”
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Estimating Homophily in Social Networks Using Dyadic Predictions by George Berry (5807582)

“…Node-level prediction models, such as the use of names to classify ethnicity or gender, do not generally produce unbiased predictions of dyad categories and therefore produce biased homophily estimates. …”

Neuro-symbolic representation learning on biological knowledge graphs by Mona Alshahrani (3576653)

“…In the past years, feature learning methods that are applicable to graph-structured data are becoming available, but have not yet widely been applied and evaluated on structured biological knowledge. …”

R²S100K: Road-Region Segmentation Dataset for Semi-supervised Autonomous Driving in the Wild by Muhammad Atif Butt (10849980)

“…Alongside, we present an Efficient Data Sampling based self-training framework to improve learning by leveraging unlabeled data. …”

Analysing Satellite Imagery Classification under Spatial Domain Shift across Geographic Regions by Sara A. Al-Emadi (22827935)

“…<p dir="ltr">Deep learning models are designed based on the i.i.d. assumption; consequently, they experience a significant performance drop due to the distribution shifts when deployed in real environments. …”