FEATURES OF LOCAL IMMUNITY IN PATIENTS WITH OROPHARYNGEAL CANCER by O. I. Keith, M. N. Tilliashaihov, P. V. Svetitsky, E. Yu. Zlatnik, G. I. Zakora, A. A. Ganiev, G. P. Nistratov

“…An important role is given to assessing the practical experience of related medical institutions.Objective: to develop an algorithm for the diagnosis and treatment of patients with oropharyngeal cancer using the experience of medical institutions dealing with these patients. …”
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Research status and progress on key technologies of intelligent orchard by CUI Hongwei, LU Xiaoxuan, YANG Yaqing, LU Xinyi, MA Hao, JI Jiangtao, JIN Xin, LI Xiuzhen, ZHAO Zimeng, ZENG Ningning

“…Future smart orchard technology will place greater emphasis on multi-source information fusion, autonomous operation of agricultural machinery, and intelligent management throughout the entire process. By deeply integrating perception data from different sources, orchard managers can more accurately grasp the production dynamics of the orchard, further improving the scientificity of decision-making. …”
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Evaluation of Knowledge Management Maturity Level in Iranian Audiovisual Archives Based on the APQC Model by Sepideh Ciruskabiri, Atefeh Sharif, Saeed Rezaei Sharifabadi, Mohammad Hassanzadeh

“…First, the number of experts familiar with advanced knowledge management models in this domain was relatively limited, which may affect the depth and accuracy of the responses provided. …”
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Prediction of early breast cancer patient survival using ensembles of hypoxia signatures. by Inna Y Gong, Natalie S Fox, Vincent Huang, Paul C Boutros

“…We demonstrate that the best way of merging preprocessing methods varies from signature to signature, and that there is likely no 'best' preprocessing pipeline that is universal across datasets, highlighting the need to evaluate ensembles of preprocessing algorithms. …”
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Enhancing Predictive Capabilities for Identifying At-Risk Stocks Using Multivariate Time-Series Classification: A Case Study of the Thai Stock Market by Katsamapol Petchpol, Laor Boongasame

“…To address data imbalance, concept drift, and long-term dependencies, the framework integrates feature engineering, cost-sensitive learning, and rolling window training. …”
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YouTube and Bilibili as sources of information on oral cancer: cross-sectional content analysis study by Qilei zhang, Zhe Li, Huiping Zhang, Ling Han, Shugang Zhao, Siyu Jia

“…YouTube videos received a greater number of views and likes, while there was no significant difference in average likes per 30 days or comments between the two platforms. …”
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Multi-View Collaborative Training and Self-Supervised Learning for Group Recommendation by Feng Wei, Shuyu Chen

“…Unlike individual recommendation, group recommendation must consider both individual preferences and group dynamics, thereby enhancing decision-making efficiency for groups. …”
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Real-world implementation and adaptation to local settings of first trimester preeclampsia screening in Italy: a systematic review by Silvia Amodeo, Giulia Bonavina, Anna Seidenari, Paolo Ivo Cavoretto, Antonio Farina

“…Early identification of pregnancies at risk of developing PE is crucial for implementing preventive strategies. …”
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PREDICTION INTERVALS IN MACHINE LEARNING: RESIDUAL BOOTSTRAP AND QUANTILE REGRESSION FOR CASH FLOW ANALYSIS by Wa Ode Rahmalia Safitri, Farit Mochamad Afendi, Budi Susetyo

“…Time series forecasting often faces challenges in producing reliable predictions due to inherent uncertainty in dynamic systems. …”
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Machine learning-based prediction of scale formation in produced water as a tool for environmental monitoring by Arash Tayyebi, Ali Alshami, Erfan Tayyebi, Ademola Owoade, MusabbirJahan Talukder, Nadhem Ismail, Zeinab Rabiei, Xue Yu, Glavic Tikeri

“…Machine learning (ML) as a data-driven method is a powerful tool for uncovering hidden patterns in experimental data necessary for decision-making on scale formation predictions by analyzing the complex relationships between mainly the water chemistry and the pH. …”
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