Application and prospect of artificial intelligence in empowering the operation and managment of oil and gas pipelines by Qi LIAO, Chunying LIU, Jian DU, Hao LAN, Yongtu LIANG, Haoran ZHANG

“…AI methodologies have found extensive application across various research domains, largely focusing on leak detection, corrosion analysis, risk evaluation, identification, prediction, and optimization. The evolution of AI-driven research has transitioned from conventional approaches like neural networks, expert systems, fuzzy logic, and wavelet analysis towards new-generation algorithms, including deep learning, transfer learning, and reinforcement learning. …”
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Diagnosis methods for pancreatic cancer with the technique of deep learning: a review and a meta-analysis by Yuanbo Bi, Dongrui Li, Ruochen Pang, Chengxv Du, Da Li, Xiaoyv Zhao, Haitao Lv

“…Inclusion criteria were studies involving PDAC patients, using deep learning algorithms for diagnosis evaluation, using histopathological results as the reference standard, and having sufficient data. …”
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Differential chemoproteomic analysis of RRS-1 candidate molecule and molecules of several nonsteroidal anti-inflammatory drugs by P. A. Galenko-Yaroshevsky, I. Yu. Torshin, A. N. Gromov, O. A. Gromova, K. F. Suzdalev, R. A. Murashko, A. V. Zelenskaya, A. V. Zadorozhniy, T. R. Glechyan, G. V. Simavonyan, E.M. I. Muhammad

“…Chemoproteomic modeling of pharmacological effects of RRS-1 molecule and a number of well-known NSAIDs (diclofenac, nimesulide, ketorolac) on human proteome was carried out on the basis of numerical prediction algorithms over the space of heterogeneous feature descriptions, developed in the topological approach to recognition by Yu.I. …”
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Relationship between stress hyperglycemia ratio and the incidence of atrial fibrillation in patients after coronary artery bypass grafting: a retrospective study based on the MIMIC... by Runjia Liu, Jiatong Li, Jing Zeng, Yuxuan Tao, Dong Chen, Haixia Li

“…Incorporating SHR into post-CABG risk assessment enhances AF prediction, offering a valuable reference for clinical decision-making. …”
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Integrated Bioinformatics and Experimental Validation Reveal Macrophage Polarization-Related Biomarkers for Osteoarthritis Diagnosis by He Q, Liu L, Hu X, Lin L, Song Z, Xia Y, Lin Q, Wei J, Li S

“…Additionally, various analyses, including immune infiltration, gene set enrichment analysis, competing endogenous RNA (ceRNA) construction, and drug prediction, were conducted. Finally, clinical samples were clinically validated through RT-qPCR (OA: Control = 10: 5) and IHC (6: 5) experiments.Results: Three hub genes (MYC, SIK1, and NFIL3) were identified, and the diagnostic model constructed using them demonstrated good diagnostic efficacy in both internal and external datasets (internal AUC = 0.965, external AUC = 0.847). …”
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Development of a Diagnostic Model for Focal Segmental Glomerulosclerosis: Integrating Machine Learning on Activated Pathways and Clinical Validation by Ge Y, Liu X, Shu J, Jiang X, Wu Y

“…We then developed a highly accurate diagnostic model by integrating nine machine learning algorithms into 101 combinations, achieving near-perfect AUC values across training, validation, and external cohorts. …”
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ATP6V0A4 as a novel prognostic biomarker and potential therapeutic target in oral squamous cell carcinoma by Xiaopu Gao, Jiamin Zhou, Yu Qiao, Chuyin Lin, Guanxiong Zhang, Qiuyu Wu, Zhikang Su, Qianji Zhang, Songkai Huang

“…Further, immunotherapy response prediction models and drug sensitivity analysis were utilized to define therapeutic potential. …”
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Genetic variants of the DLK1, KISS1R, MKRN3 genes in girls with precocious puberty by E. A. Sazhenova, O. Yu. Vasilyeva, E. A. Fonova, M. B. Kankanam Pathiranage, A. Yu. Sambyalova, E. E. Khramova, L. V. Rychkova, S. A. Vasilyev, I. N. Lebedev

“…The pathogenicity of identified genetic variants and the functional significance of the protein synthesized by them were analyzed according to recommendations for interpretation of NGS analysis results using online algorithms for pathogenicity prediction (Variant Effect Predictor, Franklin, Varsome, and PolyPhen2). …”
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New machine-learning models outperform conventional risk assessment tools in Gastrointestinal bleeding by Eszter Boros, József Pintér, Roland Molontay, Kristóf Gergely Prószéky, Nóra Vörhendi, Orsolya Anna Simon, Brigitta Teutsch, Dániel Pálinkás, Levente Frim, Edina Tari, Endre Botond Gagyi, Imre Szabó, Roland Hágendorn, Áron Vincze, Ferenc Izbéki, Zsolt Abonyi-Tóth, Andrea Szentesi, Vivien Vass, Péter Hegyi, Bálint Erőss

“…We analyzed the prospective, multicenter Hungarian GIB Registry’s data. The predictive performance of XGBoost and CatBoost machine-learning algorithms with the Glasgow-Blatchford (GBS), pre-endoscopic Rockall and ABC scores were compared. …”
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Preoperative digital 6-minute walk test reveals risk of postoperative pulmonary complications in patients undergoing heart valve surgery: a pilot feasibility study by Lixuan Li, Yuqiang Wang, Zhengbo Zhang, Zeruxin Luo, Wenqing Wang, Jiachen Wang, Xiaoli Liu, Ying Shi, Tian Yuan, Yong Fan, Hong Liang, Yingqiang Guo, Buqing Wang, Jing Wang, Jiaoxue Deng

“…We extracted 94 physiological features across 6MWT phases (baseline, walking, recovery) and clinical variables, developing predictive models using five machine learning algorithms evaluated through rigorous five-fold cross-validation. …”
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Revisiting Southern Gallo-Romance from a complexity theory standpoint: Occitan by Jean Léo Léonard

“…In this paper, the inner structure of the Occitan dialect network is revisited in the light of a range of cumulative (Ward’s method) vs. reductive (Complete linkage, Groupe Average, Weighted Average) hierarchical algorithms provided by Gabmap, an Online dialectometric application for calculating distance/similarities by edit distance (Levenshtein algorithm). …”
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Monitoring of Thoracopulmonary Compliance During High-Frequency Jet Ventilation: Theoretical and Practical Aspects by M. B. Kontorovich, B. D Zislin, A. V. Chistyakov, A. V. Markov

“…The clinical tests of the developed algorithms permitted a new assessment of the physiological essence of thoracopulmonary compliance during HFJV. …”
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A machine learning‐based approach for wait‐time estimation in healthcare facilities with multi‐stage queues by Amjed Al‐Mousa, Hamza Al‐Zubaidi, Mohammad Al‐Dweik

“…The work employs feature engineering and compares several machine learning‐based algorithms to predict patients' waiting times for single‐stage and multi‐stage services. …”
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External validation of the PAR-Risk Score to assess potentially avoidable hospital readmission risk in internal medicine patients. by Lukas Higi, Angela Lisibach, Patrick E Beeler, Monika Lutters, Anne-Laure Blanc, Andrea M Burden, Dominik Stämpfli

“…Univariable logistic regression was used to predict potentially avoidable readmissions (PARs), as identified by the SQLape algorithm. …”
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IRGL-RRI: interpretable graph representation learning for plant RNA–RNA interaction discovery by Qingquan Liao, Xuchong Liu, Wei Zhao, Yu Tong, Fangzheng Xu, Xinxin Liu, Yifan Chen

“…To address this, this study proposes an interpretable graph representation model for accurate plant RRI prediction. The model enriches sample information by extracting features of different bases from plant RNA data and reconstructs these features using an algorithmic hierarchy approach to capture more complex patterns. …”
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A simple and efficient plasticity-fracture constitutive model for confined concrete by Hadi Meidani

“…A plasticity-fracture constitutive model is presented for prediction of the behavior of confined plain concrete. …”
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Artificial intelligence techniques applications in the wastewater: A comprehensive review by Zakur Yahya, Márquez Fausto, Al-Taie Ali, Alsaidi Saif, Alsadoon Abeer, Mirashrafi Seyed Bagher, Flaih Laith, Zakoor Yousif

“…Also, the review discusses the application of the various (AI) algorithms on the various wastewater treatment plants (WWTPs), predicting (“WWTP”) effluent properties, the wastewater inflows, the anomaly detecting, and the energy optimization. …”
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Engineering project management technology based on visual simulation module and particle swarm optimization by Hua Tian

“…The particle swarm multi-objective optimization algorithm performed well in reducing project cost prediction errors. …”
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Comparative study on inversion of the unsaturated hydraulic parameters using optimization and Bayesian estimation methods by KE Fengqiao, MAN Jun, ZENG Lingzao, WU Laosheng

“…However, this method is sensitive to the initial guess of parameters, and the obtained predictions occasionally deviate from the measurements. 2) The MCMC algorithm can provide state predictions which better fit measurements. …”
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Identifying key drivers of heatwaves: A novel spatio-temporal framework for extreme event detection by J. Pérez-Aracil, C. Peláez-Rodríguez, Ronan McAdam, Antonello Squintu, Cosmin M. Marina, Eugenio Lorente-Ramos, Niklas Luther, Verónica Torralba, Enrico Scoccimarro, Leone Cavicchia, Matteo Giuliani, Eduardo Zorita, Felicitas Hansen, David Barriopedro, Ricardo García-Herrera, Pedro A. Gutiérrez, Jürg Luterbacher, Elena Xoplaki, Andrea Castelletti, S. Salcedo-Sanz

“…This research can potentially enhance our understanding of HW drivers and predictability.…”
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