Detection of breast cancer using machine learning and explainable artificial intelligence by Tharunya Arravalli, Krishnaraj Chadaga, H Muralikrishna, Niranjana Sampathila, D. Cenitta, Rajagopala Chadaga, K. S. Swathi

“…The research emphasized the results obtained by explainers such as SHAP (SHapley Additive exPlanations), LIME (Local Interpretable Model-agnostic Explanations), ELI5 (Explain Like I’m Five), Anchor and QLattice (Quantum Lattice) to decipher the findings. Interpretable algorithms can be applied in the medical sector to assist practitioners in predicting breast cancer, reducing diagnostic errors, and improving clinical decision-making.…”
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Plausible Vehicle Trajectory Augmentation With Hybrid Machine Learning by Junyeop Park, Hyeonsoo Jang, Byeongju Kang, Yunhyoung Hwang

“…A crucial factor in achieving these outcomes is the accurate prediction of surrounding vehicle trajectories, which relies on the effective application of artificial intelligence and machine learning algorithms. …”
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Artificial Neural Network Model for Monitoring Oil Film Regime in Spur Gear Based on Acoustic Emission Data by Yasir Hassan Ali, Roslan Abd Rahman, Raja Ishak Raja Hamzah

“…Feed-forward and recurrent Elman neural network algorithms were used to develop ANN models, which are subjected to training, testing, and validation process. …”
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FastGEMF: Scalable High-Speed Simulation of Stochastic Spreading Processes Over Complex Multilayer Networks by Mohammad Hossein Samaei, Faryad Darabi Sahneh, Caterina Scoglio

“…It introduces an event-driven algorithm with cautious update strategies, supporting diverse multi-compartment spreading processes. …”
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Modeling and long-term forecasting of CO2 emissions in Asia: An optimized Artificial Neural Network approach with consideration of renewable energy scenarios by Erfan Abbasian Hamedani, S. Talebi

“…After preprocessing the data, a 5-6-1 MLP-ANN that is optimized with two metaheuristic algorithms (PSO and GWO) is utilized to train and validate the model for each country. …”
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Adaptative Pressure Estimation and Control Architecture for Integrated Electro-Hydraulic Brake System by Zhenhai Gao, Yi Yang, Guoying Chen, Liang Yuan, Jianguang Zhou, Jie Zhang

“…The fusion strategy is mainly based on the prediction performance of two algorithms under different vehicle speeds, pressures, and ABS states. …”
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Current application, possibilities, and challenges of artificial intelligence in the management of rheumatoid arthritis, axial spondyloarthritis, and psoriatic arthritis by Emre Bilgin

“…In axSpA, AI-driven models using imaging techniques such as sacroiliac radiography, magnetic resonance imaging, and computed tomography have increased diagnostic accuracy, especially for early inflammatory changes. Predictive algorithms help stratify and predict disease outcomes, while clinical decision support systems integrate clinical and imaging data for optimized management. …”
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Novel Cuproptosis-Related Gene Signature for Precise Identification of High-Risk Populations in Low-Grade Gliomas by Ping Chen, Hailing Han, Xuejie Wang, Bing Wang, Zhanfeng Wang

“…LASSO and Cox regressions were employed to filter cuproptosis-associated genes and construct prediction models. The accuracy of the predictive models was measured by using TCGA internal validation set and the CGGA external validation set. …”
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ACD-ML: Advanced CKD detection using machine learning: A tri-phase ensemble and multi-layered stacking and blending approach by Mir Faiyaz Hossain, Shajreen Tabassum Diya, Riasat Khan

“…This study aims to leverage machine learning algorithms and ensemble models for early detection of CKD using the “Chronic Kidney Disease (CKD15)” and “Risk Factor Prediction of Chronic Kidney Disease (CKD21)” datasets from the UCI Machine Learning Repository. …”
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Dynamic Collaborative Optimization Method for Real-Time Multi-Object Tracking by Ziqi Li, Dongyao Jia, Zihao He, Nengkai Wu

“…On the MOT17 test set, it achieves 63.7% in HOTA, 61.4 FPS in processing speed, and 79.4% in IDF1, outperforming current state-of-the-art tracking algorithms.…”
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Event recognition technology and short-term rockburst early warning model based on microseismic monitoring and ensemble learning by Zibin Li, Dengpan Qiao, Tianyu Yang, Jun Wang, Hao Chen

“…The rockburst early warning model V-soft achieves peak accuracy and F1 scores of 0.9394 and 0.9173, respectively, demonstrating performance improvements of 6.59–15.68% in accuracy and 14.11–27.21% in F1 score compared to conventional machine learning algorithms and ensemble classifiers. This highlights its superior discriminative capability and robustness in predicting high-intensity rockburst events. …”
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Nondestructive Detection of Rice Milling Quality Using Hyperspectral Imaging with Machine and Deep Learning Regression by Zhongjie Tang, Shanlin Ma, Hengnian Qi, Xincheng Zhang, Chu Zhang

“…Among single-task models, BPNNs outperformed the others in predicting BRR and HRR, with correlation coefficients (<i>r</i>) up to 0.9. …”
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Deep Mining on the Formation Cycle Features for Concurrent SOH Estimation and RUL Prognostication in Lithium-Ion Batteries by Dongchen Yang, Weilin He, Xin He

“…By integrating diverse datasets with advanced algorithms and models, we perform correlation analyses of parameters such as capacity, voltage, temperature, pressure, and strain, enabling precise SOH estimation and RUL prediction. …”
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Advancing Hydrogel-Based 3D Cell Culture Systems: Histological Image Analysis and AI-Driven Filament Characterization by Lucio Assis Araujo Neto, Alessandra Maia Freire, Luciano Paulino Silva

“…<b>Background:</b> Machine learning is used to analyze images by training algorithms on data to recognize patterns and identify objects, with applications in various fields, such as medicine, security, and automation. …”
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CareNexus: Integrated solutions for Healthcare Communication by Alexandru Ioan BULZAN

“…A secure authentication based on multiple factors and the use of encryption algorithms, an interface based on different user roles and a prediction system based on model training had been implemented. …”
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Information extraction from green channel textual records on expressways using hybrid deep learning by Jiaona Chen, Jing Zhang, Weijun Tao, Yinli Jin, Heng Fan

“…As the results, it is discovered that the text features extracted from pre-training substantially enhance the prediction accuracy of deep learning algorithms. Surprisingly, the RoBERTa model is highly effective in the task for the expressway green channel NER. …”
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Fault Diagnosis and Prognosis With Inferential Sensors: A Hybrid Approach Integrating Symbolic Regression and Information Theory by Efi Safikou, Krishna R. Pattipati, George M. Bollas

“…We propose a fault diagnosis approach that integrates symbolic regression and information theory to optimize inferential sensors, which, along with traditional detection techniques and hard sensors, contribute to a comprehensive fault detection and diagnosis algorithm. Additionally, we introduce an advanced predictive scheme to estimate time-dependent fault evolution functions that enable us to compute the remaining useful life (RUL) of the system. …”
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Carbon stock dynamics of forest to oil palm plantation conversion for ecosystem rehabilitation planning by D. Frianto, E. Sutrisno, A. Wahyudi, E. Novriyanti, W.C. Adinugroho, A.S. Yunianto, H. Kurniawan, H. Khotimah, A. Windyoningrum, I.W.S. Dharmawan, H.L. Tata, S. Suharti, H.H. Rachmat, E.M. Lim

“…Data analysis was carried out using Classification and Regression Tree, a decision tree algorithm used in machine learning for guided classification. …”
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THE APPROVAL OF COMPLEX TREATMENT EFFECTIVENESS OF GENERALIZED PERIODONTITIS FOR THE PATIENTS AFTER TRANSMITTED CORONAVIRUS DISEASE AND REMAIN ON REHABILITATION by T.I. Matviykiv, M.M. Rozhko

“…Examination of areas compromised by generalized periodontitis and abutment teeth based on the obtained periotestometric data of tooth mobility, indicates a significant reduction in inflammation and strengthening of the ligaments and is a highly informative diagnostic method. …”
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Calculation Model of Multi-roll Straightening Process Based on Bilinear Hardening and Power Hardening by ZHU Xiaoyu, CHENG Zixing, WANG Xiaogang, HAN Peisheng

“…The results show that with increasing reduction, the error between hardened and ideal models increases. …”
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