Perineural invasion in pancreatic cancer: proteomic analysis and in vitro modelling by Wasfi Alrawashdeh, Richard Jones, Laurent Dumartin, Tomasz P. Radon, Pedro R. Cutillas, Roger M. Feakins, Branko Dmitrovic, Ihsan Ekin Demir, Guralp O. Ceyhan, Tatjana Crnogorac‐Jurcevic

“…Perineural invasion (PNI) is a common and characteristic feature of pancreatic ductal adenocarcinoma (PDAC) that is associated with poor prognosis, tumor recurrence, and generation of pain. …”
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An Automated Compliance Framework for Critical Infrastructure Security Through Artificial Intelligence by Sardar Muhammad Ali, Abdul Razzaque, Muhammad Yousaf, Rafi Us Shan

“…Attributes were extracted using the Term Frequency-Inverse Document Frequency (TF-IDF) technique and refined through Recursive Feature Elimination (RFE). A content-based filtering (CBF) recommender system, aligned with organizational maturity levels, was developed and enhanced with a feedback loop for user insights. …”
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Mendelian Randomization Analysis Reveal the Role of Circulating Inflammatory Proteins in Mediating Functional Brain Networks and Peripheral Neuropathic Pain Effects by Wen‐Hui Liu, Hui‐Min Hu, Chen Li, Qing Shi, Yi‐Fan Li, Peng Mao, Bi‐Fa Fan

“…Methods: The resting‐state functional magnetic imaging phenotype is defined as a stable feature that quantifies the pattern of functional connectivity (i.e., synchronized activity) between different regions of the brain in the resting state of an individual. …”
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Local Outlier Detection Method Based on Improved K-means by Yu ZHOU, Hao XIA, Xuezhen YUE, Peichong WANG

“…The task of outlier detection involves identifying these points and analyzing their potential abnormal information through the analysis of data attribute features. This process aims to uncover unusual patterns or behaviors within the dataset that can provide insights into unique phenomena or anomalies. …”
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Bridge Deflection Separation Prediction Model Based on DWT-LSTM and Its Engineering Application by ZHENG Shuai, JIANG He, WANG Zhongchang, DING Jia, YANG Yi

“…Thirdly, based on the decomposed deflection components and external factors, two LSTM-based time series prediction models were developed: a multi-factor model for noise deflection and a single-factor model for trend deflection. …”
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Improving ICESat-2 photon classification and tree height estimation using Moran's I and machine learning by Mei-Kuei Lu, Sorin Popescu, Lonesome Malambo

“…Random Forest models were developed and compared, with one model incorporating Moran's I to capture spatial patterns. …”
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Examining the role of semiotics in social media-driven information campaigns by Mayor Inna Gurung, Nitin Agarwal

“…Engagement was measured by likes, while diffusion patterns followed the SEIZ epidemiological model. Findings show that posts featuring SCP symbols consistently received more interaction, even when follower counts were equal. …”
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Advances in Bract Coloration: Diversity, Pigment Synthesis, and Regulatory Mechanisms in Ornamental Plants by Xiaoyang Li, Yang Liu, Zhiquan Cai, Yiwei Zhou

“…Despite these advances, significant knowledge gaps remain in genetic inheritance patterns, epigenetic regulation, cross-pigment pathway crosstalk, and environmental modulation. …”
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An Explainable Hybrid CNN–Transformer Architecture for Visual Malware Classification by Mohammed Alshomrani, Aiiad Albeshri, Abdulaziz A. Alsulami, Badraddin Alturki

“…Visual malware classification, which transforms malware binaries into grayscale images, has emerged as a promising alternative for recognizing patterns in malicious code. This study presents a hybrid deep learning architecture that combines the local feature extraction capabilities of ConvNeXt-Tiny (a CNN-based model) with the global context modeling of the Swin Transformer. …”
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Automated multi-class MRI brain tumor classification and segmentation using deformable attention and saliency mapping by Erfan Zarenia, Amirhossein Akhlaghi Far, Khosro Rezaee

“…This model effectively captures irregular and complex tumor patterns, enhancing classification performance. Following classification, a comprehensive segmentation process was conducted across a large dataset, reinforcing the model’s role as a decision support system. …”
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Graph convolutional neural networks improved target-specific scoring functions for cGAS and kRAS in virtual screening by Bo Wang, Muhammad Junaid, Wenjin Li

“…This indicates that the graph convolutional network can be generalized to the prediction of heterogeneous data based on the complex patterns of molecular protein binding that have been learned. …”
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A hybrid approach to predicting and classifying dental impaction: integrating regularized regression and XG boost methods by Asok Mathew, Pradeep K. Yadalam, Ahmed Radeideh, Shrouk Hady, Rona Swed, Reyyan Cheema, Majd Mousa AL-Mohammad, Mohammed Alsaegh, SR Shetty

“…Advanced predictive models like logistic Regression and XGBoost analyze critical variables, identify patterns, and perform predictive analysis. These models can identify potential impactions, assess impaction type, and develop treatment plans. …”
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Vibration mitigation in interlocking metasurfaces by O. Bolmin, P.J. Noell, N. Leathe, B.L. Boyce

“…Interlocking metasurfaces (ILMs) are a new class of mechanical metamaterials with patterned surface features that enable joining of two adjacent bodies, serving as an alternative to welds, fasteners, or adhesives. …”
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Enhancing prediction of crop yield and soil health assessment for sustainable agriculture using machine learning approach by Kapil Netaji Vhatkar, Shweta Ashish Koparde, Sonali Kothari, Jayesh Sarwade, Kishor Sakur

“…Back-propagation Neural Network (BPNN) is an SL algorithm applied for predicting complex patterns, especially in crop yield and soil health assessments. …”
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Forecasting Temperature Time Series Data Using Combined Statistical and Deep Learning Methods: A Case Study of Nairobi County Daily Temperature by John Kamwele Mutinda, Amos Kipkorir Langat, Samuel Musili Mwalili

“…In addition, the high R-squared value of 0.779234 indicates that approximately 77.92% of the variance in the observed data is explained by the model, showcasing its robustness and effectiveness in capturing the underlying patterns in temperature time series data. Overall, this study underscores the importance of VMD in preprocessing data to enhance feature representation and forecasting accuracy. …”
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Surface Damage Detection in Hydraulic Structures from UAV Images Using Lightweight Neural Networks by Feng Han, Chongshi Gu

“…The developed DL-based model integrates an enhanced Fast-SCNN backbone for efficient feature extraction, a Lightweight Feature Pyramid Attention (LFPA) module for multi-scale context enhancement, and an Edge Attention Module (EAM) for refined boundary localization. …”
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Improved chaotic fruit fly optimization with elman neural network based data-driven approach on product reviews classification by Mohammed Alghamdi, Najla I. Al-shathry, Yahia Said, Hasan Beyari, Shaymaa Sorour, Khalid Nazim Abdul Sattar, Fouad Shoie Alallah, Abdulrhman Alshareef

“…Yet, predicting the correct sentiment difference in customer feedback is challenging due to complicated logic, sequence length, and text pattern adjustments. This article focuses on designing and developing Enhanced NLP with Data-driven Product Reviews Classification using the improved chaotic fruit fly optimization (ENLPPR-ICFFO) method. …”
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An enhanced fusion of transfer learning models with optimization based clinical diagnosis of lung and colon cancer using biomedical imaging by N. A. S. Vinoth, J. Kalaivani, R. Madonna Arieth, S. Sivasakthiselvan, Gi-Cheon Park, Gyanendra Prasad Joshi, Woong Cho

“…Furthermore, fusion models such as CapsNet, EffcientNetV2, and MobileNet-V3 Large are employed for the feature extraction. The FTLMO-BILCCD technique implements a hybrid of temporal pattern attention and bidirectional gated recurrent unit (TPA-BiGRU) for classification. …”
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A topology-guided high-quality solution learning framework for security-constraint unit commitment based on graph convolutional network by Liqian Gao, Lishen Wei, Shichang Cui, Jiakun Fang, Xiaomeng Ai, Wei Yao, Jinyu Wen

“…Firstly, a GCN-based method is presented to learn the potential patterns between commitments and graph data associated with bus feature and power grid topology. …”
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Dichotomous intronic polyadenylation profiles reveal multifaceted gene functions in the pan-cancer transcriptome by Jiao Sun, Jin-Young Kim, Semo Jun, Meeyeon Park, Ebbing de Jong, Jae-Woong Chang, Sze Cheng, Deliang Fan, Yue Chen, Timothy J. Griffin, Jung-Hee Lee, Ho Jin You, Wei Zhang, Jeongsik Yong

“…The application of this workflow to RNA-seq data from The Cancer Genome Atlas demonstrated that this dichotomous intronic APA pattern is a consistent feature in transcriptomes across both normal tissues and various cancer types. …”
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