Development and validation of novel machine learning-based prognostic models and propensity score matching for comparison of surgical approaches in mucinous breast cancer by Chunmei Chen, Jundong Wu, Yutong Fang, Yong Li, Qunchen Zhang

“…We have successfully developed 6 optimal prognostic models utilizing the XGBoost algorithm to accurately predict the survival of MBC patients. …”
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Comparative Analysis of Automated Machine Learning for Hyperparameter Optimization and Explainable Artificial Intelligence Models by Muhammad Salman Khan, Tianbo Peng, Hanzlah Akhlaq, Muhammad Adeel Khan

“…The study focuses on predicting the ultimate moment capacity of Ultra-High-Performance Concrete (UHPC) beams and U-shaped girders. …”
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The BRCA1 variant p.Ser36Tyr abrogates BRCA1 protein function and potentially confers a moderate risk of breast cancer. by Charita M Christou, Andreas Hadjisavvas, Maria Kyratzi, Christina Flouri, Ioanna Neophytou, Violetta Anastasiadou, Maria A Loizidou, Kyriacos Kyriacou

“…PolyPhen algorithm predicted that the BRCA1 p.Ser36Tyr VUS identified in the Cypriot population was damaging, whereas Align-GVGD predicted that it was possibly of no significance. …”
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Application of Artificial Intelligence in Tinnitus Diagnosis and Treatment: A Pilot Study by Yu Wang, Kaixiang Pan, Richard Tyler, Zhaoyi Lu, Shan Xiong, Yufei Xie, Tao Pan

“…We describe the curation of the input data, the algorithm (CTGan) used to extend the dataset, and the ML model (Random Forest) to predict each of the suggested treatments. …”
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Development of an Intelligent Tablet Press Machine for the In-Line Detection of Defective Tablets Using Machine Learning and Deep Learning Models by Sun Ho Kim, Su Hyeon Han

“…The TPM was verified by sorting defective tablets in-line using a pretrained defect-detection algorithm. <b>Results:</b> The RF model demonstrated the highest predictive accuracy at 93.7% with an Area Under the Curve (AUC) of 0.895, while the ANN model achieved an accuracy of 92.6% with an AUC of 0.878. …”
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Enhancing Campus Mobility: Simulated Multi-Objective Optimization of Electric Vehicle Sharing Systems Within an Intelligent Transportation System Frameworks by Omar S. Aba Hussen, Shaiful J. Hashim, Nasri Sulaiman Member, S.A.R. Alhaddad, Bassam Y. Ribbfors, Masanobu Umeda, Keiichi Katamine

“…A simulation model was developed in MATLAB, utilizing the Non-dominated Sorting Genetic Algorithm (NSGA-II), a powerful multi-objective optimization technique that balances conflicting objectives to achieve the best trade-offs for operational efficiency. …”
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Optimization Design Method of a 6-DOF Micromanipulation Mechanism for Extreme Ultraviolet Projection Lithography Objective Lens by Shiyu Li, Junbo Liu, Ji Zhou, Haifeng Sun, Chuan Jin, Xia Kang, Song Hu

“…The results demonstrate a 15.1% reduction in maximum driving force, significantly enhancing outrigger driving smoothness.…”
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Investigating the Use of Machine Learning Models to Understand the Drugs Permeability Across Placenta by Vaisali Chandrasekar, Mohammed Yusuf Ansari, Ajay Vikram Singh, Shahab Uddin, Kirthi S. Prabhu, Sagnika Dash, Souhaila Al Khodor, Annalisa Terranegra, Matteo Avella, Sarada Prasad Dakua

“…Owing to limited drug testing possibilities in pregnant population, the development of computational algorithms is crucial to predict the fate of drugs in the placental barrier; it could serve as an alternative to animal testing. …”
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INTELLECTUAL POTENTIAL OF A REGION: APPRAISAL AND CONTROL TOOL IN INNOVATIVE ACTIVITY by O. Loseva

“…It is suggested that the entropy of particular indicators should be taken into account when calculating summary rating in order to increase ranking reliability.The tool of control over the region’s intellectual potential quality in innovation is shown, the former comprising the following tools of diagnostics and monitoring: 1) system of indicators of intellectual potential characterizing its state in the areas that are crucial for effective innovation, i. e. innovation and entrepreneurship, research and cultural-educational ones; 2) procedure of the intellectual potential quality estimation, based on determination of integral rankings, carried out according to the level of development and stability of the indicator values of a particular region within the system of other regions, and taking into account indicators entropy; 3) factor analysis algorithm of the intellectual potential dynamics on the basis of the index method.The paper sets the guidelines for of use of the obtained results in the interests of the region’s innovation development and anticipated effects from their practical implementation: financial, budgetary, administrative, general economic effects.The conclusion is made that methodology for appraisal of intellectual potential and the tool of control over its quality can be effectively applied in order to stir up innovation in the region.…”
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Legal aspects of applying indexes and e-management in evaluating the publication activity of scientists by R. O. Omorov

“…The Hirsch index is calculated from the number of citations of the researcher’s works included in a certain database.For CIS countries, an important database of scientific and educational publications is the database of the Russian Scientific Citation Index (RSCI). …”
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Investigating Internet of Things and Artificial Intelligence-Based Approaches to Smart Irrigation System Optimisation for Agricultural Water Resource Management by Balassem Zaid Ajzan, Alkhafaij Mahdi Abdulkhudur, Raju Nadimpalli Venkata Ganapathi

“…This system leverages IoT sensors to monitor environmental variables and uses AI algorithms to analyze this data and make real-time irrigation decisions. …”
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Toward reliable fluorescence imaging: Optical prior-guided probabilistic reconstruction for structured illumination microscopy by Kun Lin, Junkang Dai, Huaian Chen, Yi Jin

“…Fluorescence microscopy is expected to be a reliable technique for bioprocess analysis, but the current single, deterministic imaging cannot objectively reflect the inherent observation errors caused by instruments and algorithms. For structured illumination microscopy (SIM) used for fast and long-term imaging at low excitation levels, the risk of unreliable misconceptions will be more non-negligible due to severe noise and super-resolution reconstruction. …”
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Trends in indirect liver function marker testing in Wales from 2000 to 2017 and their association with age and sex: an observational study by Joe West, Joanne R Morling, Trevor Alexander Hill, Colin John Crooks

“…AST and ALT values varied by age and sex, particularly in males with the upper normal range of ALT values decreasing rapidly from 90 U/L at age 30 to 45 U/L by age 80.Conclusion The reduction in AST testing to only 1% of the adult population limits the use of many non-invasive liver marker algorithms. …”
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“Making” Rural Elites: Empowerment of Chinese Rural “Public Affairs Live Streamers” on Short Video Platforms by Yayun Tong, Zhenghua Zhang, Yuxiao Wang

“…However, their empowerment is constrained by the platform’s algorithm distribution mechanisms and opaque content regulation, making the conversion of capital unstable, traffic-dependent, and challenging to sustain. …”
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Inheritance and protection of intangible cultural heritage in drama category based on AI human–computer interaction and digital technology by Jingjing Ren

“…The model uses a Higher-Order Graph Neural Network (HOGNN) combined with an attention mechanism and Low-Rank Adaptation (LoRA) algorithm to construct a dynamic relational network. …”
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Integrated Ultrasound‐Enrichment and Machine Learning in Colorimetric Lateral Flow Assay for Accurate and Sensitive Clinical Alzheimer's Biomarker Diagnosis by Shuqing Wang, Yan Zhu, Zhongzeng Zhou, Yong Luo, Yan Huang, Yibiao Liu, Tailin Xu

“…The LFA device is integrated with a portable ultrasonic actuator to rapidly enrich microparticles using ultrasound, which is essential for sample pre‐enrichment to improve the sensitivity, followed by ML algorithms to classify and predict the enhanced colorimetric signals. …”
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The role of advanced machine learning in COVID-19 medical imaging: A technical review by Abdul Muiz Fayyaz, Said Jadid Abdulkadir, Shahab Ul Hassan, Safwan Mahmood Al-Selwi, Ebrahim Hamid Sumiea, Lareib Fatima Talib

“…It focuses on approaches such as Deep Learning (DL) algorithms and Transfer Learning, which have demonstrated significant potential in developing automated, accurate COVID-19 detection systems. …”
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Systematic Security Analysis of Sensors and Controls in PV Inverters: Threat Validation and Countermeasures by Fengchen Yang, Kaikai Pan, Chen Yan, Xiaoyu Ji, Wenyuan Xu

“…These vulnerabilities can lead to incorrect sensor readings, disrupting control algorithms. We propose an IEMI attack that results in three potential outcomes: Denial of Service (DoS), physical damage to the inverter, and power output reduction. …”
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Hybrid neural network method for damage localization in structural health monitoring by Fatahlla Moreh, Yusuf Hasan, Zarghaam Haider Rizvi, Sven Tomforde, Frank Wuttke

“…Many existing methods for crack detection rely on deep learning algorithms or traditional approaches that typically use image data. …”
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Evaluation and optimization of carbon emission for federal edge intelligence network by Peng ZHANG, Yong XIAO, Jiwei HU, Liang LIAO, Jianxin LYU, Zegang BAI

“…In recent years, the continuous evolution of communication technology has led to a significant increase in energy consumption.With the widespread application and deep deployment of artificial intelligence (AI) technology and algorithms in telecommunication networks, the network architecture and technological evolution of network intelligent will pose even more severe challenges to the energy efficiency and emission reduction of future 6G.Federated edge intelligence (FEI), based on edge computing and distributed federated machine learning, has been widely acknowledged as one of the key pathway for implementing network native intelligence.However, evaluating and optimizing the comprehensive carbon emissions of federated edge intelligence networks remains a significant challenge.To address this issue, a framework and a method for assessing the carbon emissions of federated edge intelligence networks were proposed.Subsequently, three carbon emission optimization schemes for FEI networks were presented, including dynamic energy trading (DET), dynamic task allocation (DTA), and dynamic energy trading and task allocation (DETA).Finally, by utilizing a simulation network built on real hardware and employing real-world carbon intensity datasets, FEI networks lifecycle carbon emission experiments were conducted.The experimental results demonstrate that all three optimization schemes significantly reduce the carbon emissions of FEI networks under different scenarios and constraints.This provides a basis for the sustainable development of next-generation intelligent communication networks and the realization of low-carbon 6G networks.…”
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