Artificial intelligence demonstrates potential to enhance orthopaedic imaging across multiple modalities: A systematic review by Umile Giuseppe Longo, Alberto Lalli, Guido Nicodemi, Matteo Giuseppe Pisani, Alessandro De Sire, Pieter D'Hooghe, Ara Nazarian, Jacob F. Oeding, Balint Zsidai, Kristian Samuelsson

“…Among the studies included in the final synthesis, Convolutional Neural Networks (CNN) emerged as the most frequently applied category of ML models, present in 17 studies (32%). …”
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Towards prehospital risk stratification using deep learning for ECG interpretation in suspected acute coronary syndrome by Frederik M Zimmermann, Pim A L Tonino, Arjan Koks, Jesse P A Demandt, Marcel van ’t Veer, Pieter-Jan Vlaar, Thomas P Mast, Konrad A J van Beek, Marieke C V Bastiaansen

“…Objectives Most patients presenting with chest pain in the emergency medical services (EMS) setting are suspected of non-ST-elevation acute coronary syndrome (NSTE-ACS). …”
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GAN-enhanced deep learning for improved Alzheimer's disease classification and longitudinal brain change analysis by Purushottam Pandey, Surbhi Bhatia Khan, Surbhi Bhatia Khan, Surbhi Bhatia Khan, Jyoti Pruthi, Eid Albalawi, Ali Algarni, Ahlam Almusharraf

“…The ResNet101 model is augmented with innovative layers such as the pattern descriptor parsing operation (PDPO) and the detection convolutional kernel layer (DCK), which are designed to extract the most relevant features from datasets such as ADNI and OASIS. …”
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Deep Learning and Image Generator Health Tabular Data (IGHT) for Predicting Overall Survival in Patients With Colorectal Cancer: Retrospective Study by Seo Hyun Oh, Youngho Lee, Jeong-Heum Baek, Woongsang Sunwoo

“…Three models were developed and compared: a conventional artificial neural network (ANN), a basic convolutional neural network (CNN), and a transfer learning–based Visual Geometry Group (VGG)16 model. …”
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Research on Atlantic surface pCO2 reconstruction based on machine learning by Jiaming Liu, Jie Wang, Xun Wang, Yixuan Zhou, Runbin Hu, Haiyang Zhang

“…Notably, the Copernicus pCO2 and CODC-GOSD pCO2 contribute the most, with both contributing ∼0.72. These are followed by TP, latitude, longitude, SHWW, U10, and E. (2) After comprehensive data testing, the six machine learning models select the optimal hyperparameters for reconstruction. …”
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Research on Data Repair of Pile-Type Adjustable Wind Turbine Foundation Monitoring Based on FST-ATTNet by WEI Huanwei, ZHAO Jizhang, ZHENG Xiao, TAN Fang, LIU Cong

“…In the spatial domain, the Temporal Convolutional Network (TCN) models long-range dependencies by expanding causal convolutions, thereby capturing local and global spatial relationships. …”
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Irrigated rice-field mapping in Brazil using phenological stage information and optical and microwave remote sensing by Andre Dalla Bernardina Garcia, MD Samiul Islam, Victor Hugo Rohden Prudente, Ieda Del’Arco Sanches, Irene Cheng

“…Analytic results show that the end of season is the most suitable for obtaining a reliable classification based on optical and SAR sensors. …”
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Artificial Intelligence for Detecting COVID-19 With the Aid of Human Cough, Breathing and Speech Signals: Scoping Review by Mouzzam Husain, Andrew Simpkin, Claire Gibbons, Tanya Talkar, Daniel Low, Paolo Bonato, Satrajit S. Ghosh, Thomas Quatieri, Derek T. O'Keeffe

“…Half of the publications and Apps were from the USA. The most prominent AI architecture used was a convolutional neural network, followed by a recurrent neural network. …”
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Improved Surface Electromyogram-Based Hand–Wrist Force Estimation Using Deep Neural Networks and Cross-Joint Transfer Learning by Haopeng Wang, He Wang, Chenyun Dai, Xinming Huang, Edward A. Clancy

“…However, prior studies focused mostly on applying TL within one joint, which limits dataset size and diversity. …”
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Accuracy of artificial intelligence in caries detection: a systematic review and meta-analysis by Alexander Maniangat Luke, Nader Nabil Fouad Rezallah

“…The meta-analysis incorporates fourteen of the 21 articles included in this review. The research mostly uses convolutional neural networks (CNNs) for analyzing images, showing outstanding accuracy, sensitivity, and specificity in detecting caries. …”
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Intelligent decision-making and regulation method of gas extraction “borehole-pipe network” system by Kai WANG, Dongxu WANG, Aitao ZHOU, Junwen ZHANG, Fangzhou SONG, Chang’ang DU, Yushuang HAO, Xihui FAN, Wei ZHAO

“…The results show that Long Short-Term Memory (LSTM) has the highest matching degree with gas extraction data features among the four prediction algorithms, and the improved Convolutional Neural Network- Long Short-Term Memory (CNN-LSTM) model can effectively improve the problem of LSTM over-reliance on time series. …”
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Category semantic and global relation distillation for object detection by Yanpeng LIANG, Zhonggui MA, Zongjie WANG, Zhuo LI

“…Object detection, a fundamental task in computer vision, has witnessed remarkable success in domains such as autonomous driving, robotics, and facial recognition, owing to advancements in convolutional neural networks. Despite these successes, state-of-the-art models for object detection often come with a high number of parameters, pushing the limits of modern hardware and posing challenges for deployment on devices with limited resources. …”
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Synthesizing field plot and airborne remote sensing data to enhance national forest inventory mapping in the boreal forest of Interior Alaska by Pratima Khatri-Chhetri, Hans-Erik Andersen, Bruce Cook, Sean M. Hendryx, Liz van Wagtendonk, Van R. Kane

“…To achieve this goal, we compared the performance of two advanced modeling approaches, the convolutional neural network (CNN) and the XGBoost model. …”
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Forecasting Short- and Long-Term Wind Speed in Limpopo Province Using Machine Learning and Extreme Value Theory by Kgothatso Makubyane, Daniel Maposa

“…Seasonal wind speed analysis revealed distinct patterns, with winter emerging as the most efficient season for wind, featuring a median wind speed of 7.96 m/s. …”
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Multimodal diagnosis of Alzheimer’s disease based on resting-state electroencephalography and structural magnetic resonance imaging by Junxiu Liu, Junxiu Liu, Shangxiao Wu, Shangxiao Wu, Shangxiao Wu, Qiang Fu, Qiang Fu, Xiwen Luo, Xiwen Luo, Yuling Luo, Yuling Luo, Sheng Qin, Sheng Qin, Yiting Huang, Yiting Huang, Zhaohui Chen, Zhaohui Chen

“…However, the inclusion of electroencephalography (EEG) in such multimodal studies has been relatively limited. Moreover, most multimodal studies on AD use convolutional neural networks (CNNs) to extract features from different modalities and perform fusion classification. …”
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Anomaly Detection Algorithms for Real-Time Log Data Analysis at Scale by Andras Horvath, Andras Olah, Attila Pinter, Balint Siklosi, Gergely Lukacs, Istvan Z. Reguly, Kalman Tornai, Tamas Zsedrovits, Zoltan Mathe

“…Our results underscore the importance of selecting the right balance between sophistication and simplicity, challenging the assumption that the most sophisticated methods are necessary for effective anomaly detection in real-world log data.…”
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NDVI Estimation Throughout the Whole Growth Period of Multi-Crops Using RGB Images and Deep Learning by Jianliang Wang, Chen Chen, Jiacheng Wang, Zhaosheng Yao, Ying Wang, Yuanyuan Zhao, Yi Sun, Fei Wu, Dongwei Han, Guanshuo Yang, Xinyu Liu, Chengming Sun, Tao Liu

“…RGB images were used to extract conventional features, including color indices (CIs), texture features (TFs), and vegetation coverage, while convolutional features (CFs) were extracted using the deep learning network ResNet50 to optimize the model. …”
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Enhancing head and neck cancer detection accuracy in digitized whole-slide histology with the HNSC-classifier: a deep learning approach by Haiyang Yu, Haiyang Yu, Wang Yu, Wang Yu, Yuan Enwu, Yuan Enwu, Yuan Enwu, Jun Ma, Jun Ma, Xin Zhao, Xin Zhao, Linlin Zhang, Linlin Zhang, Linlin Zhang, Fang Yang, Fang Yang, Fang Yang

“…Head and neck squamous cell carcinoma (HNSCC) represents the sixth most common cancer worldwide, with pathologists routinely analyzing histological slides to diagnose cancer by evaluating cellular heterogeneity, a process that remains time-consuming and labor-intensive. …”
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The Study of Roadside Visual Perception in Internet of Vehicles Based on Improved YOLOv5 and CombineSORT by LI Xiaohui, YANG Jie, XIA Qin

“…In this process, the loss is calculated based on the differences in length, width, and diagonal between the detection and ground-truth boxes, and batch normalization (BN) layer sparsification is applied for convolutional channel filtering. Secondly, combining DeepSORT, StrongSORT and Bot-SORT, a new method of CombineSORT is presented for multi target tracking. …”
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Lightweight Apple Leaf Disease Detection Algorithm Based on Improved YOLOv8 by LUO Youlu, PAN Yonghao, XIA Shunxing, TAO Youzhi

“…[Objective]As one of China's most important agricultural products, apples hold a significant position in cultivation area and yield. …”
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