Application of graph theory in liver research: A review by Xumei Hu, Longyu Sun, Rencheng Zheng, Xueqin Xia, Meng Liu, Weibo Chen, Xinyu Zhang, Chengyan Wang

“…Graph theory can be used to analyze liver networks and identify altered nodes and edges, which may serve as potential noninvasive biomarkers for disease detection. …”
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How can we make robot dance expressive and responsive? A survey of methods and future directions by Benedikte Wallace, Benedikte Wallace, Kyrre Glette, Kyrre Glette, Alex Szorkovszky

“…By mapping out current methods and challenges, we aim to provide insights that may guide future innovations in creating more engaging, responsive, and expressive robotic systems.…”
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Predicting Court Judgment in Criminal Cases by Text Mining Techniques by Mohammad Farhadishad, Mohammad Kazemifard, Zahra Rezaei

“…Due to high pressures and stress, it may be difficult for them to carefully examine documents and evidence, which leads to more subjective judgments. …”
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Harvester Maintenance Prediction Tool: Machine Learning Model Based on Mechanical Features by Rodrigo Oliveira Almeida, Richardson Barbosa Gomes da Silva, Danilo Simões

“…In default mode, we ran 25 popular algorithms through the database and compared them based on accuracy and error metrics. …”
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Characterization of the immune cell infiltration patterns in lung adenocarcinoma to facilitate immunotherapy by Haili Li, Zanmei Qin, Xuemei Huang, Zuyou Wei, JingMin Deng

“…Herein, ESTIMATE and CIBERSORT algorithms were conducted to characterize the ICI patterns of 1155 patients with LUAD. …”
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Synergistic frameworks for sensor fault isolation and accommodation in grid-side converters by Faizan Mehmood, Lenos Hadjidemetriou, Panayiotis M. Papadopoulos, Marios M. Polycarpou

“…Although sensor fault detection algorithms are usually effective under abrupt faults, the fault propagation effect caused by the physical interconnection between the DC and AC sides of the converter may limit the performance of the sensor fault isolation process in revealing the exact location of a potential faulty sensor. …”
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Target identification of natural products in cancer with chemical proteomics and artificial intelligence approaches by Guohua Li, Qian Shi, Qibiao Wu, Xinbing Sui

“…AI-driven models, especially machine learning algorithms, have proven effective in processing complex proteomic data and predicting potential NP-protein interactions. …”
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Water quality prediction using LSTM with combined normalizer for efficient water management by N. Mahesh, J. Jagan Babu, K. Nithya, S.A. Arunmozhi

“…Predicting water quality is a significant area of study in the field of smart water technology, since it may provide valuable assistance in managing and mitigating water pollution. …”
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Ankrd1 as a potential biomarker for the transition from acute kidney injury to chronic kidney disease by Hailin Li, Lemei Hu, Changqing Zheng, Ying Kong, Ming Liang, Quhuan Li

“…This study indicated that the upregulation of Ankrd1 was positively associated with the progression from AKI to CKD and may potentially serve as a valuable biomarker for this transitional process.…”
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Survey on Effective Disposal of E-Waste to Prevent Data Leakage by Akila Victor, Gurunathan Arunkumar, Rajendran Kannadasan, Soundrapandiyan Rajkumar, Ramani Selvanambi

“…Disposing of this e-waste is not so simple, as it may contain a significant amount of intellectual property in the form of data. …”
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Evaluation of PPG Feature Values Toward Biometric Authentication Against Presentation Attacks by Shun Hinatsu, Daisuke Suzuki, Hiroki Ishizuka, Sei Ikeda, Osamu Oshiro

“…Several approaches have been proposed to apply PPG to biometric authentication using a wearable device; however, there may be several attacks against PPG-based authentication. …”
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RODA-OOD: Robust Domain Adaptation from Out-of-Distribution Data by Jaekyun Jeong, Mangyu Lee, Sunguk Yun, Keejun Han, Jungeun Kim

“…In practice, Out-Of-Distribution (OOD) data which do not share labels with the existing data may also be collected during the target data collection process. …”
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Explainable AI Methods for Underwater Mine Warfare by Guy Junior Richard, Jerome Habonneau, Didier Gueriot, Jean-Marc Le Caillec

“…Artificial intelligence (AI) has brought new algorithms providing high performance compared to the usual methods. …”
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Hybrid optimization of thermally-enhanced Zn-Fe LDH catalysts for fenton-like reactions: Integrating design of experiments with machine learning models for optimisation by Ramadhan Muhammad Naufal, Nawwal Hikmah, Dessy Ariyanti

“…This study presents a novel hybrid modeling framework that combines Response Surface Methodology (RSM) with machine learning (ML) algorithms– Support Vector Regression (SVR) and Gradient Boosting Regression (GBR)– to contribute to the predictive modeling and optimization of thermally-activated ZnFe-LDH based Fenton catalysis. …”
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Improving thyroid disorder diagnosis via innovative stacking ensemble learning model by Ayesha Hassan, Shabana Ramzan, Ali Raza, Muhammad Munwar Iqbal, Aseel Smerat, Norma Latif Fitriyani, Muhammad Syafrudin, Seung Won Lee

“…Objective Hypothyroidism, hyperthyroidism, thyroid nodules, and other thyroid disorders are common around the world, affect millions of people worldwide, and untreated health conditions may lead to serious health issues. An accurate and timely diagnosis serves as crucial for proper management and medication. …”
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3D Reconstruction of the Human Colon From Capsule Endoscope Video by Pal Anders Floor, Ivar Farup, Marius Pedersen

“…To help reduce the workload, tools from computer vision may be helpful. In this paper, we investigate the possibility of constructing 3D models of whole sections of the human colon using image sequences from wireless capsule endoscope video, providing improved visualization as well as position localization of pathologies for gastroenterologists. …”
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Atrial Tachyarrhythmias and Atrial Flutter: the Basics of Diagnostics and Modern Opportunities of Therapy by Yu. A. Bunin, S. A. Miklishanskaya, E. A. Zolozova, V. V. Chigineva

“…Based on these recommendations, clear algorithms for the management of patients with atrial tachyarrhythmias are given. …”
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Precision Medicine in Lung Cancer Screening: A Paradigm Shift in Early Detection—Precision Screening for Lung Cancer by Hsin-Hung Chen, Yun-Ju Wu, Fu-Zong Wu

“…However, implementation must also address challenges related to health equity, algorithmic bias, and system integration. As precision medicine continues to evolve, it holds the promise of optimizing early detection, minimizing harm, and extending the benefits of lung cancer screening to broader and more diverse populations. …”
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The Fractality of Sentiment Arcs for Literary Quality Assessment: the Case of Nobel Laureates by Yuri Bizzoni, Pascale Moreira, Mads Rosendahl Thomsen, Kristoffer L. Nielbo

“…Lastly, we perform another experiment to examine whether arc fractality may be used to distinguish more or less popular works within the Nobel canon itself, looking at the probability of higher GoodReads’ ratings at different levels of arc fractality. …”
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Prediction of volcanic fractures based on prestack azimuthal anisotropy: A case study of LFS area in southern Songliao Basin by LI Ning,MIAO He,CAO Kaifang

“…Anisotropic parameter inversion based on pre-stack azimuth gather seismic data is one of the primary methods for fracture prediction, among which two algorithms, RüGER approximate equation and Fourier series expansion, are more widely used. …”
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