Modeling the variables that influence substance consumption of people who experience homelessness in Colombia by Leandro González Támara, Sandra Patricia Barragán Moreno

“…While results reveal strong associations, they do not imply causality. …”
Get full text

Architectural Exploration and Performance Enhancement of the CVA6 RISC-V Core Using the Gem5 Simulation Framework by Umer Shahid, Muhammad Tahir, Bilal Zafar, Ayesha Ahmad, Shanzay Wasim, Bisal Saeed

“…To further enhance the architecture, we integrated machine learning algorithms to optimize performance and resource efficiency. …”
Get full text

Real-Time Polarimetric Imaging and Enhanced Deep Learning Model for Automated Defect Detection of Specular Additive Manufacturing Surfaces by Dingkang Li, Xing Peng, Hongbing Cao, Yuanpeng Xie, Shiqing Li, Xiang Sun, Xinjie Zhao

“…Defect detection technology remains a research focus in AM process monitoring. While machine learning and neural network algorithms have recently achieved significant advancements in innovative applications for AM defect detection, practical implementations still face challenges, including insufficient detection accuracy and poor system robustness. …”
Get full text

Multimodal fusion radiomic-immunologic scoring model: accurate identification of prostate cancer progression by Zhonglin Zhang, Huan Liu, Xiling Gu, Yang Qiu, Jiangqing Ma, Guangyong Ai, Xiaojing He

“…This included the Akaike Information Criterion (AIC), Maximum Relevance Minimum Redundancy (mRMR), and Least Absolute Shrinkage and Selection Operator (LASSO) algorithms, validated through 10-fold cross-validation. …”
Get full text

A deep learning and IoT-driven framework for real-time adaptive resource allocation and grid optimization in smart energy systems by Arvind R. Singh, M. S. Sujatha, Akshay D. Kadu, Mohit Bajaj, Hailu Kendie Addis, Kota Sarada

“…Traditional energy management methods, based on static models or heuristic algorithms, often fail to handle real-time grid dynamics, leading to suboptimal energy distribution, high operational costs, and significant energy wastage. …”
Get full text

Evaluating Network Performance in a Web-Based Augmented Reality System for Lipmatte Color Recommendation by Zulfikri Paidi, Nurhanna Md Abd Wahid, Nurzaid Muhd Zain, Mahfudzah Othman

“…This research highlights the significant potential of AR technology in modernizing the beauty shopping experience while illustrating the critical role of network performance in achieving optimal user satisfaction. …”
Get full text

Leveraging ensemble convolutional neural networks and metaheuristic strategies for advanced kidney disease screening and classification by Abeer saber, Esraa Hassan, Samar Elbedwehy, Wael A. Awad, Tamer Z. Emara

“…DL models are designed to focus on problems, whereas TL uses the knowledge acquired while resolving one issue to another pertinent issue. …”
Get full text

Enhancing seizure detection with hybrid XGBoost and recurrent neural networks by Santushti Santosh Betgeri, Madhu Shukla, Dinesh Kumar, Surbhi B. Khan, Muhammad Attique Khan, Nora A. Alkhaldi

“…This study investigates machine learning and deep learning algorithms for seizure prediction, comparing their effectiveness on a large EEG dataset of epileptic patients. …”
Get full text

Simplifying the calibration of ecological models by using the parameter estimation tool (PEST): The Curonian Lagoon case by Burak Kaynaroglu, Mindaugas Zilius, Rasa Idzelytė, Artūras Razinkovas-Baziukas, Georg Umgiesser

“…Data from the second-year were used for model calibration, while first-year observations served for the validation of the model's performance in simulating nutrient dynamics. …”
Get full text

Unveiling the role of oxidative stress in ANCA-associated glomerulonephritis through integrated machine learning and bioinformatics analyses by Liyuan Xie, Xianying Qiu, Junya Jia, Tiekun Yan, Pengcheng Xu

“…It’s to be noted that RAC2 and ITGB2 were associated with cyclophosphamide in the AAGN glomerular compartment, while VCAM1 and VEGFA were associated with dexamethasone in the tubulointerstitial compartment. …”
Get full text

Advancement of Artificial Intelligence in Cost Estimation for Project Management Success: A Systematic Review of Machine Learning, Deep Learning, Regression, and Hybrid Models by Md. Mahfuzul Islam Shamim, Abu Bakar bin Abdul Hamid, Tadiwa Elisha Nyamasvisva, Najmus Saqib Bin Rafi

“…Hybrid models combine the strengths of different algorithms, achieving 80–90% accuracy on average, and are particularly effective in complex, multi-faceted projects. …”
Get full text

Analyzing Post-fire Vegetation Dynamics with Ultra-high Resolution Remote Sensing Data by O. Petrov, O. Petrov, A. Medvedev

“…Co-alignment was applied to multi-temporal UAV datasets, and tree segmentation was performed using the algorithms developed for Airborne Laser Scanning (ASL) forest point clouds. …”
Get full text

Exploring the potential role of ENPP2 in polycystic ovary syndrome and endometrial cancer through bioinformatic analysis by Xumin Zhang, Jianrong Liu, Chunmei Bai, Yang Li, Yanxin Fan

“…Methods Initially, differential analysis, the least absolute shrinkage and selection operator (LASSO) regression, and support vector machine-recursive feature elimination (SVM-RFE) algorithms were employed to identify candidate genes associated with ferroptosis in PCOS. …”
Get full text

Modeling residue formation from crude oil oxidation using tree-based machine learning approaches by Mohammad-Reza Mohammadi, Seyyed-Mohammad-Mehdi Hosseini, Behnam Amiri-Ramsheh, Saptarshi Kar, Ali Abedi, Abdolhossein Hemmati-Sarapardeh, Ahmad Mohaddespour

“…Furthermore, temperature was identified as the most influential factor affecting residual crude oil content, exhibiting a significant negative correlation, while API gravity also showed a negative impact. …”
Get full text

Deep Learning Approaches for Retinal Disease Identification in Fundus Imaging: A Comprehensive Overview by Ismael Abdulkareem Ali, Sozan Abdullah Mahmood

“…Vision impairment is becoming a major health concern, especially in elderly people. While in the medical field, manually detecting ocular pathology has significant difficulty. …”
Get full text

Design of an intelligent AI-based multi-layer optimization framework for grid-tied solar PV-fuel cell hybrid energy systems by Prashant Nene, Dolly Thankachan

“…RL-ENN stands for Reinforcement Learning-Driven Evolutionary Neural Network, while T-STFREP is a generalized acronym for Transformer-Based Spatiotemporal Forecasting. …”
Get full text

The Improved-EFI Score: A Multi-Omics-Based Novel Efficacy Predictive Tool for Predicting the Natural Fertility of Endometriosis Patients by He Q, Zhang C, Hu Y, Deng J, Zhang S

“…An improved endometriosis fertility index (EFI) predictive model was created based on ultrasound radiomics and urinary proteomics gathered during the patient’s initial admission, using two machine learning algorithms. The predictive model was evaluated for C-index, calibration, and clinical applicability through receiver working characteristic curve, decision curve analysis.Results: The improved EFI prediction model nomogram, based on five ultrasound radiomics parameters and three urine proteomics, had AUC values of 0.921 (95% CI: 0.864– 0.978) and 0.909 (95% CI: 0.852– 0.966) in the training and validation sets, respectively, while the traditional EFI prediction model had AUC values of 0.889 (95% CI: 0.832– 0.946) and 0.873 (95% CI: 0.816– 0.930) in the training and validation sets, respectively. …”
Get full text

Critical structural and functional roles for the N-terminal insertion sequence in surfactant protein B analogs. by Frans J Walther, Alan J Waring, Jose M Hernandez-Juviel, Larry M Gordon, Zhengdong Wang, Chun-Ling Jung, Piotr Ruchala, Andrew P Clark, Wesley M Smith, Shantanu Sharma, Robert H Notter

“…Gel electrophoresis demonstrated that Super Mini-B was dimeric in SDS detergent-polyacrylamide, while Mini-B was monomeric. Surface plasmon resonance (SPR), predictive aggregation algorithms, and molecular dynamics (MD) and docking simulations further suggested a preliminary model for dimeric Super Mini-B, in which monomers self-associate to form a dimer peptide with a "saposin-like" fold. …”
Get full text

Interpretable machine learning models for predicting in-hospital mortality in patients with chronic critical illness and heart failure: A multicenter study by Min He, Yongqi Lin, Siyu Ren, Pengzhan Li, Guoqing Liu, Liangbo Hu, Xueshuang Bei, Lingyan Lei, Yue Wang, Qianghong Zhang, Xiaocong Zeng

“…The MIMIC datasets served as the derivation cohort, while the eICU-CRD dataset was used for external validation. …”
Get full text

M3S-GRPred: a novel ensemble learning approach for the interpretable prediction of glucocorticoid receptor antagonists using a multi-step stacking strategy by Nalini Schaduangrat, Hathaichanok Chuntakaruk, Thanyada Rungrotmongkol, Pakpoom Mookdarsanit, Watshara Shoombuatong

“…Abstract Accelerating drug discovery for glucocorticoid receptor (GR)-related disorders, including innovative machine learning (ML)-based approaches, holds promise in advancing therapeutic development, optimizing treatment efficacy, and mitigating adverse effects. While experimental methods can accurately identify GR antagonists, they are often not cost-effective for large-scale drug discovery. …”
Get full text