A Hybrid Transfer Learning Approach to Teeth Diagnosis Using Orthopantomogram Radiographs by Ahmed Alabd-Aljabar, Zain Raisan, Mohammed Adnan, Salam Dhou

“…The results revealed that all ten chosen deep learning models experienced a similar or improved performance when used in conjunction with a machine learning classifier. …”
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Early Warning of Axillary Lymph Node Metastasis in Breast Cancer Patients Using Multi-Omics Signature: A Machine Learning-Based Retrospective Study by Ke Z, Shen L, Shao J

“…The AUC of GLRM was 0.818 (95% CI: 0.757~0.879), significantly lower than that of RFM’s AUC 0.893 (95% CI: 0.836~0.950).Conclusion: The prediction models based on machine learning (ML) algorithms and multiomics have shown good performance in predicting ALN metastasis, and RFM shows greater advantages compared to traditional GLRM. …”
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A novel network-level fused deep learning architecture with shallow neural network classifier for gastrointestinal cancer classification from wireless capsule endoscopy images by Muhammad Attique Khan, Usama Shafiq, Ameer Hamza, Anwar M. Mirza, Jamel Baili, Dina Abdulaziz AlHammadi, Hee-Chan Cho, Byoungchol Chang

“…The proposed framework offers improved accuracy, precision, and computational efficiency compared to state-of-the-art models. …”
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Artificial intelligence in dentistry—A review by Hao Ding, Jiamin Wu, Wuyuan Zhao, Jukka P. Matinlinna, Jukka P. Matinlinna, Michael F. Burrow, James K. H. Tsoi

“…This review describes the history and classification of AI, summarizes AI applications in dentistry, discusses the relationship between EBD and ML, and aims to help dental professionals better understand AI as a tool to support their routine work with improved efficiency.…”
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Approximation-Aware Training for Efficient Neural Network Inference on MRAM Based CiM Architecture by Hemkant Nehete, Sandeep Soni, Tharun Kumar Reddy Bollu, Balasubramanian Raman, Brajesh Kumar Kaushik

“…Simulation results on approximated LeNet-5, VGG8, AlexNet, and ResNet18 models trained on the CIFAR-100 dataset showed reductions of 54%, 30%, 67%, and 20% in the total number of crossbars, respectively, resulting in improved area efficiency. …”
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Enhancing Physical Layer Security in RIS-Aided HAPS for Non-Terrestrial Networks by Hanieh Memarian, S. Mohammad Razavizadeh, Ali Kuhestani

“…Simulation results demonstrate that our algorithm converges rapidly and outperforms conventional schemes that do not utilize RIS or employ random phases, achieving substantial improvements in secrecy rates. …”
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Deep deterministic policy gradient-based automatic negotiation framework for shared decision-making by Xin Chen, Ping Lu, Yong Liu, Fei-Ping Hong

“…Fuzzy membership functions are applied to model the uncertainty in patient preferences, enhancing representation and improving multi-issue negotiation outcomes. …”
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Optimizing a Dynamic Vehicle Routing Problem with Deep Reinforcement Learning: Analyzing State-Space Components by Anna Konovalenko, Lars Magnus Hvattum

“…<i>Results:</i> Our findings demonstrate that a carefully designed state space in the formulation of the DVRP significantly improves RL performance. Notably, incorporating derived features and selectively applying feature transformation enhanced the model’s decision-making capabilities. …”
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Utilising AI technique to identify depression risk among doctoral students by Changhong Teng, Chunmei Yang, Qiushi Liu

“…Based on the data from the 2019 Nature Global Doctoral Student Survey, we first screened 13 highly relevant features from a total of 37 features potentially related to the risk of depression among doctoral students by Random Forest algorithm. Subsequently, we trained the optimal prediction model to predict the doctoral students with depression risk using a Multilayer Perceptron (MLP), achieving an accuracy of 89.09% on the test set. …”
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Calculation Method of Downstream Water Level in Non-Spilling Periods of Hydropower Stations Based on Decision Tree Classification and Multiple Linear Regression by LI Yinghai, HE Liangzhe, ZHANG Hairong, NIE Panpan, QIN Hui, YANG Qingyu, GUO Jiali

“…The research findings can accurately calculate downstream water level fluctuations, reduce the impact of downstream water level on the operating head, and provide technical support for improving the refined scheduling level of hydropower stations.…”
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On differential privacy for federated learning in wireless systems with multiple base stations by Nima Tavangaran, Mingzhe Chen, Zhaohui Yang, José Mairton B. Da Silva Jr., H. Vincent Poor

“…Abstract In this work, we consider a federated learning model in a wireless system with multiple base stations and inter‐cell interference. …”
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Adaptive Window Multi-Feature Fusion Point Cloud Semantic Segmentation Network by Lie Zhu

“…The method combines dynamic and fixed window feature extraction mechanisms, using dynamic windows to model global features and fixed windows to enhance local features, effectively improving segmentation accuracy and robustness. …”
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Detecting Personally Identifiable Information Through Natural Language Processing: A Step Forward by Luca Mainetti, Andrea Elia

“…This represents an improvement of 7.47 percentage points over the current state-of-the-art model that we analyzed. …”
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Application of “high-fidelity and high-resolution” processing technology in thin reservoir identification: A case study of the deep Permian Maokou Formation in Penglai area, centra... by PENG Haotian, HE Qinglin, CHEN Kang, ZENG Ming, HE Zongqiang, TU Zhihui, KONG Lingxia, QU Bozhang

“…The final reflection coefficient model is obtained by applying regularization. Subsequently, wavelet decomposition and high-frequency wavelet replacement are conducted to expand the high-frequency spectrum while maintaining amplitude and fidelity, significantly improving seismic data resolution.Application ResultsThe test area spans 200 km², using an observation system with 24 lines, 7 sources, 270 receivers, and 180-fold coverage. …”
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ST-YOLOv8: Small-Target Ship Detection in SAR Images Targeting Specific Marine Environments by Fei Gao, Yang Tian, Yongliang Wu, Yunxia Zhang

“…Furthermore, the ST-YOLOv8 model outperforms several state-of-the-art multi-scale ship detection algorithms on both datasets. …”
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A Novel Ensemble Classifier Selection Method for Software Defect Prediction by Xin Dong, Jie Wang, Yan Liang

“…This method makes full use of the diversity characteristics of base learners, leverages their classification ability, optimizes the selection method for ensemble learning, and enhances the predictive performance of the ensemble model. The experimental results demonstrate that the DFD ensemble learning-based software defect prediction model outperforms the ten other models, including five common machine learning (ML) classification algorithms (logistic regression (LR), na&#x00EF;ve Bayes (NB), K-nearest neighbor (KNN), decision tree (DT), and support vector machine (SVM)), two deep learning (DL) algorithms (multi-layer perceptron (MLP) and convolutional neural network (CNN)), and three ensemble learning algorithms (random forest (RF), extreme gradient boosting (XGB), and stacking). …”
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Optimization of Geometric Characteristics of Cycloidal Profiles of Gerotor Hydraulic Machines by S. O. Kireev, A. R. Lebedev, M. V. Korchagina

“…The basic research method was modeling the gerotor machine profile using Mathcad computer mathematics system. …”
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Investigation of the ecology of winter plankton of Lake Baikal using complex instrumental methods by E. Yu. Naumova, T. P. Rzhepka, M. M. Makarov, A. S. Olshukov, K. M. Kucher, M. Z. Magomedova, E. S. Troitskaya

“…The obtained field data will make it possible to further improve the pattern recognition algorithm in the software of the holographic installation for the specific conditions of Lake Baikal. …”
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Assessing the Soldier Survivability Tradespace Using a Single IMU by Matthew P. Mavor, Victor C. H. Chan, Kristina M. Gruevski, Linda L. M. Bossi, Thomas Karakolis, Ryan B. Graham

“…Presented are three models based on Indoor, Section Attack (outdoors), and a General approach. …”
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Subtyping Service Receipt in Personality Disorder Services in South London: Observational Validation Study Using Latent Profile Analysis by Jack Steadman, Rob Saunders, Mark Freestone, Robert Stewart

“…ConclusionsThese results suggest that routinely collected data may be used to classify likely engagement subtypes among patients with complex needs. The algorithm identified factors associated with service use and has the potential to inform clinical decision-making to improve treatment for individuals with complex needs.…”
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