Clinical and molecular implications of cGAS/STING signaling in checkpoint inhibitor immunotherapy by Hao Chen, Yang Zhong, Yang Zhong, Rongjie Feng, Xingyu Zhu, Kang Xu, Mingjie Kuang, Wei Chong

“…Logistic and Cox regression models were utilized to investigate the association between STING signaling and checkpoint inhibitor therapeutic response. …”
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Big data and AI for gender equality in health: bias is a big challenge by Anagha Joshi, Anagha Joshi, Anagha Joshi

“…Artificial intelligence and machine learning are rapidly evolving fields that have the potential to transform women's health by improving diagnostic accuracy, personalizing treatment plans, and building predictive models of disease progression leading to preventive care. …”
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Advancing Grid-Forming Inverter Technology: Comprehensive PQ Capability and Performance Analysis by Md Nurunnabi, Shuhui Li, Himadry Shekhar Das

“…Recognizing that IBR operational constraints are distinct from those of synchronous generators, this study develops advanced PQ capability models and algorithmic frameworks that accurately characterize GFM inverter operational constraints across various coupling filter configurations (L, LC, and LCL). …”
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SD-YOLOv8: Automated Motion Detection System for Aerobics Students by Lian Tang, Ya Li, Qing Du, Jincheng Liang

“…Finally, we developed a user-friendly graphical interface using the PyQt framework, enabling visual deployment and real-time interaction with the model. Experimental results demonstrate that the improved SD-YOLOv8 achieves 97.6%, mean Average Precision (mAP) on the aerobic exercise student behavior recognition dataset, representing a 3.5% improvement over the original model. …”
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Prediction of porosity, hardness and surface roughness in additive manufactured AlSi10Mg samples. by Fatma Alamri, Imad Barsoum, Shrinivas Bojanampati, Maher Maalouf

“…These models are evaluated based on the coefficient of determination and the mean squared error. …”
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Trend equation prediction in medical and pharmaceutical studies (the example of respiratory diseases development in children in the region) by O. V. Zhukova, S. V. Kononova, T. M. Konyshkina

“…However, mathematical models and computational algorithms for monitoring, predicting incidence, spread and prevention of various nosologies are still to be developed.…”
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Enhanced pulmonary nodule detection using a transformer framework with dual fusion and gated mechanism by Kelei Sun, Yihang Wang, Huaping Zhou

“…Furthermore, a Gated Sampling and Dual Fusion Enhanced Path Aggregation Network (GDPAN) is proposed, which dynamically extracts informative features by embedding weight information into the feature maps and performs efficient multiscale fusion, thereby improving the detection of small-sized nodules. The experimental results show that GD-RTDETR increases AP, $$\hbox {AP}_{50}$$ AP 50 , $$\hbox {AP}_{75}$$ AP 75 , and $$\hbox {AP}_{S}$$ AP S by 4.1%, 1.0%, 8.1%, and 4.0%, respectively, achieving the best performance among all the models compared.…”
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SUMMARIA — A XAI Support Methodology by Generating Composite Linguistic Summaries of Qualitative Data by Carlos Rafael Rodríguez-Rodríguez, Yeleny Zulueta-Veliz, Dainys Gainza-Reyes

“…Abstract The main stream of Linguistic Data Summarization involves modeling numerical attributes using linguistic variables, which makes it difficult addressing real-world problems with qualitative or mixed data. …”
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Collaborative filtering-based Madura Island tourism recommendation system using RecommenderNet by Permana Kurniawan Eka, Rahmat Abdullah Basuki, Wicaksana Dyo Adya, Ardianto Dicky

“…The collected data were processed, formatted, and modeled using the RecommenderNet architecture, with training and validation to optimize system performance. …”
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Numerical Simulation of Earthquake Impacts on Marine Structures: A Comprehensive Review by Adel Kabi, Jersson X. Leon-Medina, Francesc Pozo

“…However, challenges persist in areas such as computational efficiency and algorithmic limitations. Key findings highlight the ability of these models to accurately simulate primary forces during seismic events and secondary effects, such as wave-induced loads. …”
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Optimizing travel time reliability with XAI: A Virginia interstate network case using machine learning and meta-heuristics by Navid Khorshidi, Shahriar Afandizadeh Zargari, Soheil Rezashoar, Hamid Mirzahossein

“…This paper applies machine learning models to predict travel time reliability in transportation networks, using XGBoost, LightGBM, and CatBoost optimized with seven metaheuristic algorithms. …”
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A Comparative Analysis of Hyper-Parameter Optimization Methods for Predicting Heart Failure Outcomes by Qisthi Alhazmi Hidayaturrohman, Eisuke Hanada

“…The XGBoost models exhibited moderate improvement (+0.01683) post-validation. …”
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Handwriting Difficulties: A Review of Recent Advances in the Identification and Intervention by Suatmi Murnani, Kazuharu Hashitsume, Tomohiko Igasaki

“…Key techniques examined include the use of spatiotemporal signals, image data, feature-extraction methods, and algorithmic classification. We also explored key experimental design elements and assistive interventions aimed at improving handwriting performance. …”
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Can Machine Learning Enhance Intrusion Detection to Safeguard Smart City Networks from Multi-Step Cyberattacks? by Jowaria Khan, Rana Elfakharany, Hiba Saleem, Mahira Pathan, Emaan Shahzad, Salam Dhou, Fadi Aloul

“…The experimental results show that the best performing model was XGB, which achieved a testing accuracy of 100% and an F1 Score of 88%. …”
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Enhancing Route Optimization in Road Transport Systems Through Machine Learning: A Case Study of the Dakhla-Paris Corridor by Najib El Karkouri, Lahcen Hassine, Younes Ledmaoui, Hasna Chaibi, Rachid Saadane, Nourddine Enneya, Mohamed El Aroussi

“…The study relies on applying advanced mathematical modeling techniques and analyzing several datasets to train various machine learning algorithms. …”
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A Novel Graph Reinforcement Learning-Based Approach for Dynamic Reconfiguration of Active Distribution Networks with Integrated Renewable Energy by Hua Zhan, Changxu Jiang, Zhen Lin

“…Traditional mathematical optimization algorithms tend to encounter issues like slow computational speed and difficulties in solving large-scale models, while heuristic algorithms are prone to fall into local optima. …”
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An Ensemble Learning Approach for Drought Analysis and Forecasting in Central Bangladesh by Md. Alomgir Hossain, Momotaz Begum, Md. Nasim Akhtar, Md. Alamin Talukder, Nomanur Rahman, Mahfuzur Rahman

“…The study revealed that integrating ARIMA with ML algorithms improved forecasting accuracy, achieving over 92.0% accuracy in predicting SPI and SPEI, thereby significantly enhancing drought prediction capabilities.…”
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Leveraging Multilingual Transformer for Multiclass Sentiment Analysis in Code-Mixed Data of Low-Resource Languages by Muhammad Kashif Nazir, Cm Nadeem Faisal, Muhammad Asif Habib, Haseeb Ahmad

“…Additionally, the proposed model outperformed other transformer-based models, as well as deep learning and machine learning algorithms in sentiment extraction from code-mixed data. …”
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Integrating Handcrafted Features with Machine Learning for Hate Speech Detection in Albanian Social Media by Fetahi Endrit, Hamiti Mentor, Susuri Arsim, Zenuni Xhemal, Ajdari Jaumin

“…To address this issue, this research aims to conduct extensive experiments using machine learning models and handcrafted feature extraction in the low-resource language Albanian. …”
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Geotri-VIO: geometrically consistent multi-prism projection for panoramic imaging in visual-inertial-odometry by Ruidong Mei, Yihan Tu, Lanxiang Zheng, MingXin Wei, Hui Cheng

“…However, the nonlinear distortions caused by the lack of geometric consistency in projection models for panoramic images pose significant challenges to feature extraction and tracking algorithms. …”
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