Refining Intra-Arterial Therapy Selection for Large Hepatocellular Carcinoma: A Deep Learning Approach Based on Covariate Interaction Analysis by An C, Li L, Luo Y, Zuo M, Liu W, Li C, Wu P

“…The DEep Learning for Interaction and Covariate Analysis in Intra-arterial Therapy SElection (DELICAITE) model integrates deep convolutional neural networks (DCNN) with covariate interaction analysis. …”
Get full text

Identification of novel metabolism-related biomarkers of Kawasaki disease by integrating single-cell RNA sequencing analysis and machine learning algorithms by Chenhui Feng, Zhimiao Wei, Xiaohui Li, Xiaohui Li

“…Our scRNA-seq data confirmed the signature genes identified by machine learning algorithms: Vimentin (VIM) and chloride intracellular channel 1 (CLIC1) were upregulated in monocytes, while integrin subunit beta 2 (ITGB2) was elevated in NK cells of KD. qRT-PCR results also validated the bioinformatic analysis. …”
Get full text

Constructing a 22-year internal wave dataset for the northern South China Sea: spatiotemporal analysis using MODIS imagery and deep learning by X. Zhang, X. Zhang, X. Li, X. Li

“…Understanding such processes necessitates the collection and analysis of extensive observational data. IWs predominantly occur in marginal seas, with the South China Sea (SCS) being one of the most active regions, characterized by frequent and large-amplitude IW activities. …”
Get full text

Deep learning-based quantitative analysis of glomerular morphology in IgA nephropathy whole slide images and its prognostic implications by Seung Yeon Cho, Yisak Kim, Sehoon Park, Jin Ho Paik, Ho Jun Chin, Jeong Hwan Park, Jung Pyo Lee, Yong-Jin Kim, Sun-Hee Park, Ho-chang Lee, Hyunjeong Cho, Beom Jin Lim, Hyung Woo Kim, Seung Hyeok Han, Heounjeong Go, Chung Hee Baek, Hajeong Lee, Kyung Chul Moon, Young-Gon Kim

Get full text

Emerging Technologies for Socioenvironmental Auditing: Identification of Factors, Challenges and Technologies Using Text Mining and Analysis by Kamakshaiah Musunuru

“…A few emerging technologies, viz., big data, blockchain, cloud computing solutions, machine learning, appear to have both a positive and a negative influence on SAP, but these are mostly insignificant. …”
Get full text

Machine Learning and Morphometric Analysis for Evaluating the Vulnerability of Tundra Landscapes to Thermokarst Hazards in the Lena Delta: A Case Study of Arga Island by Andrei Kartoziia

“…This study applies machine learning techniques to assess the vulnerability of tundra landscapes to thermokarst by integrating supervised classification using random forest with morphometric analysis based on the Topography Position Index. …”
Get full text

The "Film and Creative Engagement Project": Audiovisual Accessibility and Telecollaboration by Carmen Herrero, Karina Valverde, Tomás Costal, Alicia Sánchez-Requena

“…In the context of foreign language learning, the tasks were intended to develop participants’ skills on film analysis (such as cultural and intercultural awareness), and also, audiovisual accessibility (subtitles for the deaf and hard of hearing and audio description). …”
Get full text

MKNNet: Knowledge-aligned multimodal transformer for information retrieval by Xiaoqin Lin, Chentao Han, Jian Yao, Yue Li, Xujun Wang, Shufeng Jia

Get full text

Global burden of non-melanoma skin cancers among older adults: a comprehensive analysis using machine learning approaches by Yumeng Pan, Bo Tang, Yingwu Guo, Yuzhou Cai, Yu-Ye Li

“…However, no previous study has comprehensively analyzed these trends using integrated multi-model approaches. A comprehensive analysis of global non-melanoma skin cancer (NMSC) data from 1990 to 2021 was performed, including trend analysis, frontier analysis, and decomposition analysis to compare the burden of basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) across regions, genders, and socio-demographic groups. …”
Get full text

Multi-model radiomics and machine learning for differentiating lipid-poor adrenal adenomas from metastases using automatic segmentation by Shengnan Yin, Ning Ding, Shaocai Wang, Mengjuan Li, Yichi Zhang, Jiacheng Shen, Haitao Hu, Yiding Ji, Long Jin

“…BackgroundRadiomics based on automatic segmentation of CT images has emerged as a highly promising approach for differentiating adrenal adenomas from metastases in clinical practice; however, its preoperative diagnostic value has not been fully evaluated in previously developed methodologies.ObjectiveTo fully elucidate the diagnostic value of radiomics based on automatic segmentation techniques in differentiating adrenal adenomas from metastases through a retrospective analysis of clinical and contrast-enhanced CT (CECT) data.MethodsA retrospective analysis was conducted on the clinical and imaging data of 416 patients with adrenal masses larger than 10 mm, who had clinically indicated contrast-enhanced CT (CECT) examinations at our hospital between January 2020 and June 2024. …”
Get full text

Hierarchical RUL Prediction for Turbofan Engines Based on Health Stage Classification and Change Point-Guided Data Augmentation by Kiymet Ensarioglu

“…Two deep learning models are used for RUL prediction in engines: an LSTM model for degraded engines, which captures long-term dependencies in deterioration data, and a feature-level fusion model for healthy engines with sparse sensor data, which enhances prediction accuracy by integrating CNN and LSTM, addressing unique problems in different engine health stages. …”
Get full text

A meta-analysis for the nighttime light remote sensing data applied in urban research: Key topics, hotspot study areas and new trends by Baiyu Dong, Ruyi Zhang, Sinan Li, Yang Ye, Chenhao Huang

“…Nighttime light (NTL) data have become an essential tool for urban remote-sensing research in the past 25 years because of its ability to intuitively detect human activities. …”
Get full text

Interpretable graph Kolmogorov–Arnold networks for multi-cancer classification and biomarker identification using multi-omics data by Fadi Alharbi, Nishant Budhiraja, Aleksandar Vakanski, Boyu Zhang, Murtada K. Elbashir, Harshith Guduru, Mohanad Mohammed

“…The biomarkers identified by MOGKAN were validated as cancer-related markers through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. By integrating multi-omics data with graph-based deep learning, our proposed approach demonstrates robust predictive performance and interpretability with potential to enhance the translation of complex multi-omics data into clinically actionable cancer diagnostics.…”
Get full text

Effect of cognitive behavioral intervention on electroencephalographic band powers of children with learning difficulty under eyes-closed and eyes-open conditions by Pratima Kaushik, Samanta Puspak Kumar Jena

Get full text

Integrated Balanced Scorecard and DEA Approach for Performance Evaluation with Non-Discretionary Factors by Seyed Najafi, Mir Aryanezhad, Farhad Hosseinzadeh Lotfi, Seyyed Ebnerasoul

“…Measuring the performance of production systems is a critical management task, which the Balanced Scorecard (BSC) framework addresses by providing a clear representation of key performance indicators across financial, customer, internal process, and learning and growth perspectives. In contrast, traditional data envelopment analysis (DEA) approaches evaluate systems holistically without considering individual processes. …”
Get full text

Optimizing UK biobank cloud-based research analysis platform to fine-map coronary artery disease loci in whole genome sequencing data by Letitia M.F. Sng, Anubhav Kaphle, Mitchell J. O’Brien, Brendan Hosking, Roc Reguant, Johan Verjans, Yatish Jain, Natalie A. Twine, Denis C. Bauer

“…Aligning with the paradigm shift of bringing compute to data, we demonstrate a 44% cost reduction and 94% speedup through compute architecture optimisation on UK Biobank’s Research Analysis Platform using our RAPpoet approach. …”
Get full text

XGBoost based enhanced predictive model for handling missing input parameters: A case study on gas turbine by Nagoor Basha Shaik, Kittiphong Jongkittinarukorn, Kishore Bingi

“…This work extensively develops and evaluates an XGBoost model for predictive analysis of gas turbine performance. The goal is to construct a robust prediction model by utilizing previous operational data, such as environmental variables and operational parameters. …”
Get full text

Chemoreactomic study of fonturacetam effects: molecular mechanisms of influence on adipose tissue metabolism by O. A. Gromova, I. Yu. Torshin

“…Analysis of pharmacological capabilities of molecules within the framework of chemoreactomic methodology is carried out by comparing the chemical structure of racetam molecules with the structures of molecules for which pharmacological properties were studied using training artificial intelligence algorithms based on big data information presented in PubChem, HMDB, STRING, PharmGKB databases. …”
Get full text

A QUALITATIVE ANALYSIS OF THE INFLUENCE OF MANAGEMENT INFORMATION SYSTEMS ON ORGANIZATIONAL DECISION-MAKING PROCESSES by Mubashshir Bin Mahbub, Mushfiq Nabil, Taskin Ahmed

“…The investigation reveals six central themes that illustrate the multifaceted role of MIS: enhancing decision quality, accelerating decision-making processes, improving collaboration and communication, challenges in MIS implementation, the influence of organizational culture, and future perspectives on MIS. The analysis indicates that MIS significantly elevates decision quality by delivering real-time, accurate data and advanced analytical tools, which empower decision-makers to make informed and strategic choices. …”
Get full text

Advanced predictive machine and deep learning models for round-ended CFST column by Feng Shen, Ishan Jha, Haytham F. Isleem, Walaa J.K. Almoghayer, Mohammad Khishe, Mohamed Kamel Elshaarawy

“…Comparison with 10 analytical models demonstrates that these traditional methods, though deterministic, struggle to capture the nonlinear interactions inherent in CFST columns, thus yielding lower accuracy and higher variability. In contrast, the data-driven models presented here offer robust, adaptable, and interpretable solutions, underscoring their potential to transform design and analysis practices for CFST columns, ultimately fostering safer and more efficient structural systems.…”
Get full text