Prediction of the Ultimate Impact Response of Concrete Strengthened with Polyurethane Grout as the Repair Material by Sadi I. Haruna, Yasser E. Ibrahim, Sani I. Abba

“…The SHAP (SHapley Additive exPlanations) analysis showed that the thickness of the grouting materials and maximum load were the most significant parameters affecting the ultimate capacity of the composite U-shaped specimen. The RF model showed moderate improvements, with RF-M3 performing better than RF-M1 and RF-M2. …”
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Machine-learning of medical cannabis chemical profiles reveals analgesia beyond placebo expectations by Adi Hatav, Yelena Vysotski, Anna Shapira, Shiri Procaccia, David Meiri, Dvir Aran

“…Results Here we show that incorporating chemical composition markedly improves the prediction of pain relief (AUC = 0.63 ± 0.10) compared to models using only demographic and clinical features (AUC = 0.52 ± 0.09; p < 0.001). …”
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GE-YOLO for Weed Detection in Rice Paddy Fields by Zimeng Chen, Baifan Chen, Yi Huang, Zeshun Zhou

“…Therefore, we propose GE-YOLO to identify three common types of weeds in rice fields in the Hunan province of China and to validate its generalization performance. GE-YOLO is an improvement based on the YOLOv8 baseline model. It introduces the Neck network with the Gold-YOLO feature aggregation and distribution network to enhance the network’s ability to fuse multi-scale features and detect weeds of different sizes. …”
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Diagnostic Analysis of Crosswalk Safety Hazards in Pedestrian Environments: A SHAP-Enhanced Machine Learning Approach With Street-View Imagery by Caryl Anne M. Barquilla, Jeongwoo Lee

“…It used data from 36,750 crosswalks in Seoul, South Korea, to rigorously evaluate multiple machine learning algorithms for predicting pedestrian crash risk. Among the models assessed, the Random forest (RF) demonstrated the highest precision, aligning with the objective of enhancing pedestrian safety through accurate risk identification. …”
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Personal health data protection and intelligent healthcare applications under generative adversarial network by Xiaoyuan Gao, Wei Mi, Xirui Feng

“…Additionally, the model’s accuracy gradually improves as the privacy budget increases. …”
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Applications of artificial intelligence in neurosurgical education: a scoping review by Hector Julio Piñera-Castro, Christian Borges-García

“…However, integration requires addressing ethical dilemmas, improving multimodal data processing, and ensuring human-AI collaboration. …”
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Enhancing diabetic retinopathy detection through federated convolutional neural networks: Exploring different stages of progression by Saad Alanazi, Rayan Alanazi

“…This paper presents a comprehensive solution for DR identification utilizing deep learning algorithms. To reduce class imbalance and strengthen this model, we first prepare unbalanced data utilizing the Synthetic Minority Oversampling Technique (SMOTE). …”
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Cooling Load Forecasting Method for Central Air Conditioning Systems in Manufacturing Plants Based on iTransformer-BiLSTM by Xiaofeng Huang, Xuan Zhou, Junwei Yan, Xiaofei Huang

“…Finally, BiLSTM is applied for temporal modeling, leveraging its bidirectional recurrent structure to capture both forward and backward dependencies in time series, thereby improving forecasting accuracy. …”
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Use of satellite data for detecting icebergs and evaluating the iceberg threats by I. A. Bychkova, V. G. Smirnov

“…To assess the iceberg threat, we propose to use a model of their drif, one of the input parameters of which is the size of the detected objects. …”
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Urban heat island classification through alternative normalized difference vegetation index by N. Chanpichaigosol, C. Chaichana, D. Rinchumphu

“…The findings contribute to a deeper understanding of urban heat island effects and provide a basis for enhancing machine Learning models and urban planning frameworks. Future studies could expand to other urban areas, incorporate additional variables, and refine predictive algorithms for broader applications. …”
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Forecasting motion trajectories of elbow and knee joints during infant crawling based on long–short-term memory (LSTM) networks by Jieyi Mo, Qiliang Xiong, Ying Chen, Yuan Liu, Xiaoying Wu, Nong Xiao, Wensheng Hou

“…It experimentally explores how different input and output time-frames affect prediction accuracy and sets the stage for future research focused on optimizing models and developing effective control strategies to improve assistive crawling devices.…”
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2D Animal Skeletons Keypoint Detection: Research Progress and Future Trends by Pengfei Ma, Ronghua Gao, Qifeng Li, Qinyang Yu, Rong Wang, Chengrong Lai, Weiwei Huang, Peng Hao, Zhaoyang Wang, Xuwen Li

“…Additionally, it provides a detailed analysis of the method&#x2019;s practical application details and improvements. The paper not only summarizes different model algorithms, datasets, and evaluation metrics related to animal keypoint detection but also integrates various application scenarios, highlighting distinct features under different focal points. …”
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ARchitect: advancing architectural visualization and interaction through handheld augmented reality by Sabahat Israr, Sabahat Israr, Mudassar Ali Khan, Muhammad Shahid Anwar, Kamran Ahmad Awan, Saoucene Mahfoudh, Turki Althaqafi, Wadee Alhalabi, Wadee Alhalabi

“…The proposed approach enables users to dynamically overlay and manipulate 3D architectural elements, such as roofs, windows, and doors, within their physical environment using AR raycasting and device sensors. Algorithms supporting translation, rotation, and scaling allow precise adjustments to model placement while integrating metadata to enhance design comprehension. …”
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Building health systems capable of leveraging AI: applying Paul Farmer’s 5S framework for equitable global health by Liam G. McCoy, Azra Bihorac, Leo Anthony Celi, Matthew Elmore, Divya Kewalramani, Teddy Kwaga, Nicole Martinez-Martin, Renata Prôa, Joel Schamroth, Jonathan D. Shaffer, Alaa Youssef, Amelia Fiske

“…A broad base of critical scholarship has highlighted important issues with healthcare AI, including algorithmic bias and inequitable and inaccurate model outputs. …”
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Real-time monitoring of water quality dynamics using low-cost sensor networks in Lagos lagoon by Idowu Ayisat Aneyo, Mumin Olatunji Oladipo, Funmilayo Victoria Doherty, Julius Osato Ehigie, Adebayo Fasasi Adebari, Abdulwakeel Oluwatobi Atoyebi, Peter Ozomata Balogun, Ambrose Obinna Ikpele

“…Future research should focus on enhancing wireless communication, refining species detection algorithms and improving sensor resilience in harsh aquatic conditions.…”
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AI Dermatochroma Analytica (AIDA): Smart Technology for Robust Skin Color Classification and Segmentation by Abderrachid Hamrani, Daniela Leizaola, Nikhil Kumar Reddy Vedere, Robert S. Kirsner, Kacie Kaile, Alexander Lee Trinidad, Anuradha Godavarty

“…AIDA applies clustering techniques to classify skin tones without relying on labeled data, evaluating over twelve models, including K-means, density-based, hierarchical, and fuzzy logic algorithms. …”
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Joint Tomek Links (JTL): An Innovative Approach to Noise Reduction for Enhanced Classification Performance by Goksu Tuysuzoglu, Yunus Dogan, Elife Ozturk Kiyak, Mustafa Ersahin, Bita Ghasemkhani, Kokten Ulas Birant, Derya Birant

“…The results demonstrate that the JTL attains an average improvement of 5.33% in accuracy compared to the original classification with a random tree. …”
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Association of reproductive characteristics with osteoporosis and FRAX scores in Chinese postmenopausal women: a QCT-based cross-sectional study by Yang You, Rongkun Chang, Wenlong Qiu, Jie Cheng, Danyu Zhao, Yinbin Wang, Ruopeng Mai, Feng Chang, Lijun Cai

“…Incorporating these reproductive variables into the FRAX algorithms may improve the accuracy of identifying high-risk individuals.…”
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Enhancing decision-making on detractor-causing failures: an approach combining data mining and machine learning by Yuri A. V. da Silva, Geraldo Cardoso de Oliveira Neto, Gustavo Lima, Sidnei A. de Araújo, Rodrigo Neri Bueno da Silva, Francisco Elanio Bezerra, Marlene Amorim

“…Based on these findings, targeted action plans were developed to support continuous improvement and operational effectiveness. This research advances the state of the art by introducing an explainable AI model capable of identifying the most impactful failures affecting customer satisfaction in large-scale retail operations. …”
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ML-Based Self-Optimization Handover Technique for Beyond 5G Mobile Network by Saddam Alraih, Rosdiadee Nordin, Asma Abu-Samah, Ibraheem Shayea, Nor Fadzilah Abdullah

“…The results demonstrate that ML-SOHOT enhanced the HO optimization performance significantly and surpassed the competitive algorithms. Furthermore, ML-SOHOT achieves an average HO performance improvement of up to 96% compared to competitive algorithms from the literature. …”
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