Pooja Bidwai^1,2, Shilpa Gite^1,3, Biswajeet Pradhan^4,*, Abdullah Almari⁵

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2645-2676, 2025, DOI:10.32604/cmc.2025.061018 - 03 July 2025

Abstract Diabetic Retinopathy (DR) is a critical disorder that affects the retina due to the constant rise in diabetics and remains the major cause of blindness across the world. Early detection and timely treatment are essential to mitigate the effects of DR, such as retinal damage and vision impairment. Several conventional approaches have been proposed to detect DR early and accurately, but they are limited by data imbalance, interpretability, overfitting, convergence time, and other issues. To address these drawbacks and improve DR detection accurately, a distributed Explainable Convolutional Neural network-enabled Light Gradient Boosting Machine (DE-ExLNN) is… More >

Abu Saleh Musa Miah¹, Md Mahbubur Rahman Tusher², Md. Moazzem Hossain², Md Mamun Hossain², Md Abdur Rahim³, Md Ekramul Hamid⁴, Md. Saiful Islam⁴, Jungpil Shin^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 2573-2614, 2025, DOI:10.32604/cmes.2025.064168 - 30 June 2025

Abstract Advanced artificial intelligence technologies such as ChatGPT and other large language models (LLMs) have significantly impacted fields such as education and research in recent years. ChatGPT benefits students and educators by providing personalized feedback, facilitating interactive learning, and introducing innovative teaching methods. While many researchers have studied ChatGPT across various subject domains, few analyses have focused on the engineering domain, particularly in addressing the risks of academic dishonesty and potential declines in critical thinking skills. To address this gap, this study explores both the opportunities and limitations of ChatGPT in engineering contexts through a two-part… More >

Wei Ou^1,2,3, Shuai Liu^1,*, Mengxue Pang¹, Jianqiang Ma¹, Qiuling Yue¹, Wenbao Han¹

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 463-490, 2025, DOI:10.32604/cmc.2025.063862 - 09 June 2025

Abstract TarGuess-I is a leading model utilizing Personally Identifiable Information for online targeted password guessing. Due to its remarkable guessing performance, the model has drawn considerable attention in password security research. However, through an analysis of the vulnerable behavior of users when constructing passwords by combining popular passwords with their Personally Identifiable Information, we identified that the model fails to consider popular passwords and frequent substrings, and it uses overly broad personal information categories, with extensive duplicate statistics. To address these issues, we propose an improved password guessing model, TGI-FPR, which incorporates three semantic methods: (1) More >

Ilyas Haouam^*

Journal on Artificial Intelligence, Vol.7, pp. 85-114, 2025, DOI:10.32604/jai.2025.064145 - 27 May 2025

Abstract This study investigates the integration of Artificial Intelligence (AI) technologies—particularly natural language processing and machine learning—into qualitative research (QR) workflows. Our research demonstrates that AI can streamline data collection, coding, theme identification, and visualization, significantly improving both speed and accuracy compared to traditional manual methods. Notably, our experimental and numerical results provide a comprehensive analysis of AI’s effect on efficiency, accuracy, and usability across various QR tasks. By presenting and discussing studies on some AI & generative AI models, we contribute to the ongoing scholarly discussion on the role of AI in QR exploring its… More >

Giuseppe Carota¹, Lucia Di Pietro^2,3, Vincenzo Cardaci⁴, Anna Privitera^1,2, Francesco Bellia¹, Valentina Di Pietro⁵, Giuseppe Lazzarino¹, Barbara Tavazzi⁶, Angela Maria Amorini¹, Giacomo Lazzarino⁶, Giuseppe Caruso^6,7,*

BIOCELL, Vol.49, No.4, pp. 563-578, 2025, DOI:10.32604/biocell.2025.062176 - 30 April 2025

Abstract Carnosine (β-alanyl-L-histidine) is a naturally occurring endogenous peptide widely distributed in excitable tissues, such as the heart and brain. Over the years, several beneficial effects of carnosine have been discussed well in scientific literature. In particular, this dipeptide is well-known for its antioxidant, anti-inflammatory, and anti-aggregation activities. It is of great interest in the context of numerous systemic and neurodegenerative diseases, besides performing important “side activities” such as metal chelation and pH-buffering. Despite a plethora of preclinical and clinical data supporting carnosine’s therapeutic potential, researchers are still searching for new pharmacological targets that better highlight More >

Ali Hasan Dakheel^1,*, Mohammed Raheem Mohammed¹, Zainab Ali Abd Alhuseen¹, Wassan Adnan Hashim^2,3

Intelligent Automation & Soft Computing, Vol.40, pp. 195-220, 2025, DOI:10.32604/iasc.2025.061622 - 28 February 2025

Abstract The prediction of pregnancy-related hazards must be accurate and timely to safeguard mother and fetal health. This study aims to enhance risk prediction in pregnancy with a novel deep learning model based on a Long Short-Term Memory (LSTM) generator, designed to capture temporal relationships in cardiotocography (CTG) data. This methodology integrates CTG signals with demographic characteristics and utilizes preprocessing techniques such as noise reduction, normalization, and segmentation to create high-quality input for the model. It uses convolutional layers to extract spatial information, followed by LSTM layers to model sequences for superior predictive performance. The overall More >

DONG JIANG¹, ZHI QI³, ZHIYING XU^2,*, YIRAN LI^1,*

Oncology Research, Vol.33, No.3, pp. 709-722, 2025, DOI:10.32604/or.2024.050125 - 28 February 2025

Abstract Background: Hepatocellular carcinoma (HCC) is a prevalent liver malignancy. This study examined the roles of transforming growth factor beta (TGF-β) and cytochrome b5 domain containing 2 (CYB5D2) in HCC etiology and their prognostic biomarker potential. Methods: Key modules and prognostic genes were identified by analyzing the GSE101685 dataset by weighted gene co-expression network analysis (WGCNA) and Least absolute shrinkage and selection operator (LASSO) Cox regression. The expression levels of CYB5D2 and TGF-β in HCC cell lines were quantified using Quantitative reverse transcription polymerase chain reaction (qRT-PCR) and Western blotting (WB) assays. Effects of CYB5D2 overexpression on cell proliferation,… More >

Xinlu Zong^*, Fan Yu, Zhen Chen, Xue Xia

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 3517-3537, 2025, DOI:10.32604/cmc.2024.057494 - 17 February 2025

Abstract Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address this problem, a Multi-head Self-attention and Spatial-Temporal Graph Convolutional Network (MSSTGCN) for multiscale traffic flow prediction is proposed. Firstly, to capture the hidden traffic periodicity of traffic flow, traffic flow is divided into three kinds of periods, including hourly, daily, and weekly data. Secondly, a graph attention residual layer is constructed to learn the global spatial features across regions. Local spatial-temporal dependence is captured by using a More >

Verónica C. Tapia^1,2,*, Carlos M. Gaona²

Computer Systems Science and Engineering, Vol.49, pp. 1-17, 2025, DOI:10.32604/csse.2024.056979 - 03 January 2025

Abstract In recent years, automation has become a key focus in software development as organizations seek to improve efficiency and reduce time-to-market. The integration of artificial intelligence (AI) tools, particularly those using natural language processing (NLP) like ChatGPT, has opened new possibilities for automating various stages of the development lifecycle. The primary objective of this study is to evaluate the effectiveness of ChatGPT in automating various phases of software development. An artificial intelligence (AI) tool was developed using the OpenAI—Application Programming Interface (API), incorporating two key functionalities: 1) generating user stories based on case or process… More >

GENGYUN SUN^1,*, YIPING ZHENG^1,2, JIANFENG CAI², JIE GAO², LIE DONG², XIANGBIN ZHANG², YINGHUI HUANG^2,*

Oncology Research, Vol.33, No.1, pp. 171-184, 2025, DOI:10.32604/or.2024.047626 - 20 December 2024

Abstract Background: Long noncoding RNA, LINC01106 exhibits high expression in lung adenocarcinoma (LUAD) tumor tissues, but its functional role and regulatory mechanism in LUAD cells remain unclear. Methods: LINC01106 expression was analyzed in LUAD tissues and its functional impact on LUAD cells was assessed. LUAD cells were silenced with sh-LINC01106 and injected into nude mice to investigate tumor growth. The downstream transcription factors and molecular mechanism were determined using the Human transcription factor database (TFDB) database and Gene Expression Profiling Interactive Analysis (GEPIA) database. Additionally, the impact of linc01106 on autophagy was analyzed by determining the… More > Graphic Abstract