Diagnosis of Non-Tumor Stenosing Lesions of the Major Duodenal Papilla Using Endoscopic Ultrasonography by V. A. Belozerov, O. I. Okhotnikov, N. A. Korenevskiy, V. A. Prokopov, S. N. Grigoriev, S. M. Shevyakin

“…A therapeutic and diagnostic algorithm for the management of patients with dilation of the common bile duct has been introduced into clinical practice, based on the developed criteria for stenosis of the major duodenal papilla (MDP), for which endoscopic ultrasonography was used in combination with the methodology of synthesis of hybrid fuzzy decision rules.The algorithm was implemented in a group of patients, which included 217 people.Results. …”
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Financing investment projects in the IT sector of the Russian economy by G. A. Tarasov

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AI-enabled full-body dynamic avatar reconstruction using triboelectric smart clothing for metaverse applications by Chi Zhang, Lei Zhang, Yu Tian, Zhengang An, Bo Li, Dachao Li

“…Here, we propose AI-enabled smart clothing that seamlessly integrates triboelectric strain-sensing fibers (TSSFs) and AI algorithms with commercial fitness suits to achieve precise dynamic 3D reconstruction of body movement. …”
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Fuzzy synthetic approach for seismic risk assessment of bridges with insights from the 2023 Kahramanmaras Earthquake in Turkiye by Abdullah Ansari, Ayed E. Alluqmani, Zhongkai Huang, Jong-Han Lee, Gürkan Özden, Yewuhalashet Fissha, Taoufik Saidani, Anas Ansari

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Enhancing Pest Detection: Assessing Tuta absoluta (Lepidoptera: Gelechiidae) Damage Intensity in Field Images through Advanced Machine Learning by Edwin Lewıs, Atilla Erdinç, Yavuz Selim Şahin, Alperen Kaan Bütüner, Hilal Erdoğan

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Machine learning model design for high performance cloud computing & load balancing resiliency: An innovative approach by Nilayam Kumar Kamila, Jaroslav Frnda, Subhendu Kumar Pani, Rashmi Das, Sardar M.N. Islam, P.K. Bharti, Kamalakanta Muduli

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Predicting Insomnia Response to Acupuncture With the Development of Innovative Machine Learning by Qingyun Wan, Kai Liu, Yuyang Bo, Xiya Yuan, Mufeng Li, Xiaoqiu Wang, Chuang Chen, Lanying Liu, Wenzhong Wu

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The human-on-the-loop evaluation of multiobjective optimization algorithms for solving a real-world problem that integrates the food-energy-water nexus security and climate change... by Isaac Okola, Daniel Orwa Ochieng, Evans Kirimi Miriti, Gilbert Ouma Ong'isa

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Prediction of one-year recurrence among breast cancer patients undergone surgery using artificial intelligence-based algorithms: a retrospective study on prognostic factors by Raoof Nopour

“…The patients who were diagnosed with malignant BC and had undergone adjuvant therapies without surgery were excluded from the study. Twenty-three prognostic factors were utilized to train algorithms to establish prediction models for the one-year recurrence of breast cancer. …”
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Development and validation of a nomogram for predicting lung cancer based on acoustic–clinical features by Zhou Lu, Zhou Lu, Jiaojiao Sha, Xunxia Zhu, Xiaoyong Shen, Xiaoyu Chen, Xin Tan, Rouyan Pan, Shuyi Zhang, Shi Liu, Tao Jiang, Jiatuo Xu

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Automated Detection of the Kyphosis Angle Using a Deep Learning Approach: A Cross-Sectional Study on Young Adults by Onur Kocak, Cansel Ficici, Ilknur Ezgi Dogan, Ziya Telatar, Nihan Ozunlu Pekyavas

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Development of an integrated reactor model package for optimizing the operating modes of the sulfur production unit by Batyr Orazbayev, Nazgul Kurbangaliyeva, Kulman Orazbayeva, Ainur Zhumadillayeva, Xiaoguang Yue

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Parameter algorithm-driven optimization of surgical approaches: An investigation based on T1 slope minus C2-7 cervical lordosis in patients with cervical degenerative diseases by Tao Liu, Zhongzheng Zhi, Shuiqiang Qiu, Jian Kang, Jinhao Miao, Zhimin He, Zude Liu

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Hybrid Approach of Finite Element Method, Kigring Metamodel, and Multiobjective Genetic Algorithm for Computational Optimization of a Flexure Elbow Joint for Upper-Limb Assistive D... by Duc Nam Nguyen, Thanh-Phong Dao, Ngoc Le Chau, Van Anh Dang

“…Traditionally, an evolutionary optimization algorithm can only find one Pareto front. However, the proposed approach can generate 6 Pareto-optimal solutions, as near optimal candidates, which provides a good decision-maker. …”
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Early Detection of Voltage Instability: A Transparent, Rule-Based Method for Cyber-Resilient Grids by Mahtab Khalilifar, Seyed Mohammad Shahrtash

“…Comprehensive simulations on IEEE test systems under N-1/N-2 contingencies and load disturbances demonstrate three key advantages: 1) Early and accurate voltage stability prediction (96.8% detection accuracy), 2) Reliable identification of critical generators/loads contributing to instability, and 3) Cyber-resilient operation verified through adversarial test cases. …”
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Retracted: Prediction of stock market movement via technical analysis of stock data stored on blockchain using novel History Bits based machine learning algorithm by Nitin Nandkumar Sakhare, Imambi S. Shaik, Suman Saha

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Surrogate-Assisted Multi-Objective Optimization for Simultaneous Three-Dimensional Packing and Motion Planning Problems Using the Sequence-Triple Representation by Ziang Liu, Tomoya Kawabe, Tatsushi Nishi, Shun Ito, Tomofumi Fujiwara

“…This framework comprises three key components: solution encoding, surrogate modeling, and evolutionary computation. …”
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Analysis and Prediction of Energy Consumption Data, Using Data Mining Software by KAZOLIS Dimitrios, FANTIDIS Jacob, FOTAKIS Christos Dionyshs, TRAMANTZAS Kostantinos, TSIANTOS Vassilios

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Deep Reinforcement Learning-Based Two-Phase Hybrid Optimization for Scheduling Agile Earth Observation Satellites by Guanghui Zhou, Zhicheng Jin, Dongning Liu

“…To balance solution quality and computational efficiency, a deep reinforcement learning (DRL)-based algorithmic framework is proposed. A Markov decision process (MDP) is formulated as the foundational model for the DRL architecture. …”
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Precise irrigation of dryland cotton under canal irrigation system constraints based on the CERES-CROPGRO-Cotton model by Lei Wang, Liang He, Weihong Sun, Chen Gao, Zhenxiang Han, Meiwei Lin

“…The results indicate that the intelligent decision-making algorithm outperforms traditional methods under data limitations, reducing the irrigation water consumption-yield ratio (Ui) by 3.99 %, while increasing yield by 8.5 % to 9724 kg/ha, thus achieving both water-saving and yield-enhancing objectives. …”
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