Advanced skin cancer prediction with medical image data using MobileNetV2 deep learning and optimized techniques by Tuğçe Öznacar, Nuray Varol Kayapunar

“…These results underscore the potential of deep learning models, optimized with the memetic algorithm, to significantly improve skin cancer detection. …”
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Combining a Risk Factor Score Designed From Electronic Health Records With a Digital Cytology Image Scoring System to Improve Bladder Cancer Detection: Proof-of-Concept Study by Sandie Cabon, Sarra Brihi, Riadh Fezzani, Morgane Pierre-Jean, Marc Cuggia, Guillaume Bouzillé

“…ConclusionsThese results demonstrate the value of combining clinical and biological information, especially to improve detection of low-grade bladder cancer. Some improvements will need to be made to the automatic extraction of clinical features to make the risk factor–based model more robust. …”
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A large-scale prospective nested case-control study: developing a comprehensive risk prediction model for early detection of pancreatic cancer in the community-based ESPRIT-AI coho... by Chaoliang Zhong, Penghao Li, Jia Zhao, Xue Han, Beilei Wang, Gang Jin

“…Model training utilized a 1:20 case-control ratio, employing LASSO regression and expert opinion to select features. Multiple machine learning algorithms were compared, with the best performing algorithm selected for the final predictive model, subsequently validated using a real-world external test cohort. …”
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A Fault Diagnosis Method for Oil Well Electrical Power Diagrams Based on Multidimensional Clustering Performance Evaluation by Xingyu Liu, Xin Meng, Ze Hu, Hancong Duan, Min Wang, Yaping Chen

“…To overcome these shortcomings, this paper proposes a novel fault detection method based on the analysis of motor power parameters. …”
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GSPSO-LRF-ELM: Grid Search and Particle Swarm Optimization-Based Local Receptive Field-Enabled Extreme Learning Machine for Surface Defects Detection and Classification on the Magn... by Jun Xie, Jin Zhang, Fengmei Liang, Yunyun Yang, Xinying Xu, Junjie Dong

“…In the ELM-LRF classifier, the balance parameter C and the number of feature maps K via the GS algorithm and the initial weight Ainit via the PSO algorithm are optimized to improve the performance of the classifier. …”
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Integrating Explainable Artificial Intelligence With Advanced Deep Learning Model for Crowd Density Estimation in Real-World Surveillance Systems by Sultan Refa Alotaibi, Hanan Abdullah Mengash, Mohammed Maray, Faiz Abdullah Alotaibi, Abdulwhab Alkharashi, Ahmad A. Alzahrani, Moneerah Alotaibi, Mrim M. Alnfiai

“…This study proposes an Osprey Optimization Algorithm with Deep Learning Assisted Crowd Density Detection and Classification (OOADL-CDDC) technique for smart video surveillance systems. …”
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Machine learning-driven development of a stratified CES-D screening system: optimizing depression assessment through adaptive item selection by Ruo-Fei Xu, Zhen-Jing Liu, Shunan Ouyang, Qin Dong, Wen-Jing Yan, Dong-Wu Xu

“…Model performance was systematically evaluated through discrimination (ROC analysis), calibration (Brier score), and clinical utility analyses (decision curve analysis), with additional validation using random forest and support vector machine algorithms across independent samples. Results The resulting stratified screening system consists of an initial four-item rapid screening layer (encompassing emotional, cognitive, and interpersonal dimensions) for detecting probable depression (AUC = 0.982, sensitivity = 0.945, specificity = 0.926), followed by an enhanced assessment layer with five additional items. …”
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Evaluation of the Geomorphon Approach for Extracting Troughs in Polygonal Patterned Ground Across Different Permafrost Environments by Amin Wen, Tonghua Wu, Xiaofan Zhu, Jie Chen, Jianzong Shi, Peiqing Lou, Dong Wang, Xin Ma, Xiaodong Wu

“…The results show that (i) the lowest <i>t</i> value (0°) captured the microtopograhy of the troughs, while the larger <i>L</i> values paired with a DEM resolution of 50 cm diminished the impact of minor noise, improving the accuracy of trough detection; (ii) the optimized Geomorphon model produced trough maps with a high accuracy, achieving mIOU and F1 Scores of 0.89 and 0.90 in PB and 0.84 and 0.87 in WDL, respectively; and (iii) compared with the polygonal boundaries, the trough maps can derive the heterogeneous features to quantify the degradation of PPG. …”
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LVID-SLAM: A Lightweight Visual-Inertial SLAM for Dynamic Scenes Based on Semantic Information by Shuwen Wang, Qiming Hu, Xu Zhang, Wei Li, Ying Wang, Enhui Zheng

“…The system is based on the classic ORB-SLAM3 framework, which starts a new thread for object detection and tightly couples the semantic information of object detection with geometric information to remove feature points from dynamic objects. …”
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AAD-YOLO: An Improved YOLOv8 Model for Complex Remote Sensing Scenarios by Yue Hong, Yi Shu, Shuo Guo

“…A comparative analysis with several state-of-the-art detection algorithms further validates the effectiveness and robustness of the proposed method.…”
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A method of identification and localization of tea buds based on lightweight improved YOLOV5 by Yuanhong Wang, Yuanhong Wang, Jinzhu Lu, Jinzhu Lu, Qi Wang, Qi Wang, Zongmei Gao

“…The improved algorithm has higher detection accuracy while reducing the amount of computation and parameters. …”
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Research on Enhanced Dynamic Pig Counting Based on YOLOv8n and Deep SORT by Peng Shen, Keyu Mei, Haori Xue, Tenglong Li, Guoqing Zhang, Yongxiang Zhao, Wei Luo, Liang Mao

“…Additionally, Deep SORT is enhanced by integrating the DenseNet feature extraction network and CIoU matching algorithm, improving the accuracy and stability of target tracking. …”
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Enhancing the prediction of vitamin D deficiency levels using an integrated approach of deep learning and evolutionary computing by Ahmed Alzahrani, Muhammad Zubair Asghar

“…To improve the models effectiveness and guarantee the optimal choice of the features and hyper-parameters, we incorporate evolutionary computing methods, particularly genetic algorithms (GA). …”
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Enhanced residual attention-based subject-specific network (ErAS-Net): facial expression-based pain classification with multiple attention mechanisms by Mahdi Morsali, Aboozar Ghaffari

“…Abstract The automatic detection of pain through the analysis of facial expressions is indeed one of the most critical challenges in the healthcare system. …”
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Securing face images in UAV networks using chaos and DNA cryptography approach by Saba Inam, Shamsa Kanwal, Eaman Amin, Omar Cheikhrouhou, Monia Hamdi

“…First, edge recognition face detection technology is employed to detect facial features, with the corresponding matrix selected for encryption. …”
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YOLOv8n-WSE-Pest: A Lightweight Deep Learning Model Based on YOLOv8n for Pest Identification in Tea Gardens by Hongxu Li, Wenxia Yuan, Yuxin Xia, Zejun Wang, Junjie He, Qiaomei Wang, Shihao Zhang, Limei Li, Fang Yang, Baijuan Wang

“…The addition of the Spatial and Channel Reconstruction Convolution structure in the Backbone layer reduces redundant spatial and channel features, thereby reducing the model’s complexity. …”
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A Hybrid Network Analysis and Machine Learning Model for Enhanced Financial Distress Prediction by Saba Taheri Kadkhoda, Babak Amiri

“…Community detection algorithms are also applied to cluster companies, with the resulting labels added as categorical variables. …”
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Development and evaluation of a sensor enabled smart herbicide applicator for inter row crops by Pankaj Malkani, Indra Mani, Pramod Kumar Sahoo, Roaf Ahmad Parray, Sidhartha Sekhar Swain, Asha K．R．, Dharmender, Manojit Chowdhury, Sunil Kumar Rathod, Wahidah H․ Al-Qahtani, Ali Salem, Ahmed Elbeltagi, Abdallah Elshawadfy Elwakeel

“…The applicator integrates a weed detection system, smart sprayer, mechanical components, and power transmission system. …”
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Primary Mediastinal (Thymic) Large B-Cell Lymphoma: Experience in Treating 131 Patients at a National Medical Research Center in Russia by IZ Zavodnova, MYu Kichigina, EV Paramonova, YuE Ryabukhina, OA Kolomeitsev, OP Trofimova, NV Volkova, YuI Pryamikova, NV Kokosadze, GS Tumyan

“…This disease is characterized by specific immunomorphologic and genetic features which distinguish it from other malignant lymphoproliferative disorders with similar parameters. …”
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Intelligent Recognition Method for Ferrography Wear Debris Images Using Improved Mask R-CNN Methods by Xiangwen Xiao, Weixuan Zhang, Qing Wang, Yuan Liu, Yishou Wang

“…The accurate characterization of wear debris is crucial for assessing the health of rotating engine components and for conducting simulation experiments in debris detection. This study proposed an intelligent recognition method for ferrography wear debris images, leveraging several improved Mask Region-based Convolutional Neural Network (Mask R-CNN) algorithms to quantitatively calculate both the number of debris particles and their coverage areas. …”
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