Applications of deep learning in trauma radiology: A narrative review by Chi-Tung Cheng, Chun-Hsiang Ooyang, Chien-Hung Liao, Shih-Ching Kang

“…Diagnostic imaging is essential in modern trauma care for initial evaluation and identifying injuries requiring intervention. Deep learning (DL) has become mainstream in medical image analysis and has shown promising efficacy for classification, segmentation, and lesion detection. …”
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A novel feature extractor based on constrained cross network for detecting sleep state by Chenlei Tian, Fei Song

“…Most existing methods that utilize wrist-worn devices data for detection rely on heuristic algorithms or traditional machine learning, which suffer from low classification efficiency and insufficient accuracy. …”
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Leveraging AI for early cholera detection and response: transforming public health surveillance in Nigeria by Adamu Muhammad Ibrahim, Mohamed Mustaf Ahmed, Shuaibu Saidu Musa, Usman Abubakar Haruna, Mohammed Raihanatu Hamid, Olalekan John Okesanya, Aishat Muhammad Saleh, Don Eliso Lucero-Prisno III

“…This paper explores the potential of artificial intelligence (AI) and machine learning (ML) to address these challenges. AI technologies, including predictive modeling and ML algorithms such as random forests and convolutional neural networks (CNNs), can analyze diverse data sources—such as meteorological, environmental, and health records—to detect patterns and predict outbreaks. …”
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Quality assessment of chicken using machine learning and electronic nose by Hassan Anwar, Talha Anwar

“…This study investigates the use of an electronic nose system—a sensor array that detects odors and generates data, which is then analyzed by machine learning algorithms to predict chicken freshness. …”
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Land-cover classification in Addo Elephant National Park: Analyzing the impact of variables, classifiers, and object-based approach by Mohammad Safaei, Jane Southworth, Cerian Gibbes, Hannah V. Herrero, Mashoukur Rahaman, Bewuket B. Tefera, Jason K. Blackburn

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Integrating Machine Learning and IoT for Effective Plant Disease Management by Bhoi Manjulata, Dubey Ahilya

“…ML algorithms at the advanced level such as convolutional neural networks (CNNs) and decision trees are used to find patterns in the data which signal the presence of possible diseases in the plant. …”
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Advances in the application of machine learning technology in the field of environmental health by ZHENG Yu, LI Cheng, HU Guiping, JIA Guang

“…Among them, advanced machine learning (ML) algorithms can reveal laws that are difficult for humans to detect, showing important potential in biomarker identification, disease prevention, and environmental engineering optimization. …”
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Swincloud: a hybrid network for cloud detection in thermal infrared remote sensing images by Long Gao, Liyuan Li, Jianing Yu, Xiaoxuan Zhou, Lu Zou, Nan Fang, Xiaofeng Su, Fansheng Chen

“…Cloud cover is a significant factor affecting the effectiveness of satellite-based Earth observations. Existing cloud detection algorithms primarily rely on imaging data from satellite sensors in the visible to near-infrared spectral range, making it challenging to achieve day-and-night cloud monitoring. …”
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Comparison of ResNet-50, EfficientNet-B1, and VGG-16 Algorithms for Cataract Eye Image Classification by Ilham Santoso, Ayub Michaelangelo Manurung, Egia Rosi Subhiyakto

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Optimizing Stroke Classification with Pre-Trained Deep Learning Models by Serra Aksoy, Pinar Demircioglu, Ismail Bogrekci

“…Methods: The study utilized advanced deep learning algorithms, specifically ConvNeXt Base, to analyze large datasets of medical imaging data, focusing on MRI scans. …”
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Corn Seed Freezing Damage Identification of Different Sides Based on Hyperspectral Imaging and SPA-2DCOS Fusion Algorithm by Jun Zhang, Limin Dai, Ruiyuan Zhuang

“…In order to improve the utilization efficiency of corn seeds and meet the demand of single-seed seeding technology in agriculture, this study was conducted to explore the effect of freezing damage detection on the endosperm and embryo sides of single corn seeds, based on hyperspectral imaging combined with a feature fusion algorithm and a machine learning method. …”
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Improving Mental Health Diagnosis with Hybrid Ensemble Models: A Data-Driven Approach by Malave Sachin, Khemani Bharti, Kelkar Rucha, Balekundri Urvi, Bogar Shravani, Kolekar Areen

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The present situation and shifts observed in wetlands within the St. Lawrence Seaway region of Canada, utilizing imagery from the Landsat archive and the cloud-based platform Googl... by Meisam Amani, Mohammad Kakooei, Rebecca Warren, Sahel Mahdavi, Kevin Murnaghan, Arsalan Ghorbanian, Amin Naboureh

“…Reference samples were scrutinized using the Continuous Change Detection and Classification (CCDC) algorithm to identify spectrally unchanged samples. …”
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Building a Human Digital Twin (HDTwin) Using Large Language Models for Cognitive Diagnosis: Algorithm Development and Validation by Gina Sprint, Maureen Schmitter-Edgecombe, Diane Cook

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Deep attention model for arrhythmia signal classification based on multi-objective crayfish optimization algorithmic variational mode decomposition by Yihang Zhang, Hang Zhao

“…Many deep learning techniques are utilized for arrhythmia classification in current research but only based on ECG data, lacking the mathematical foundations of cardiac electrophysiology. …”
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An AutoEncoder enhanced light gradient boosting machine method for credit card fraud detection by Lianhong Ding, Luqi Liu, Yangchuan Wang, Peng Shi, Jianye Yu

“…This paper proposes an AutoEncoder enhanced LightGBM method for credit card detection. The method inherits the advantages of each component, using an AutoEncoder for feature reconstruction on the dataset, and integrating the LightGBM algorithm for improving the GBDT (Gradient Boosting Decison Tree) to detect abnormal data more accurately and efficiently. …”
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The Concept Design of Rice Quality Detection System Using Model-Based System Engineering Approach by Purwa Tri Cahyana, Titi Candra Sunarti, Erliza Noor, Hartrisari Hardjomidjojo, Noer Laily

“…Logical architecture diagrams were also used to structurally describe system logic to be further abstracted to the physical architecture stage. Moreover, machine learning techniques were used to simulate rice quality data analysis using the decision tree classification with the Iterative Dichotomizer 3 (ID3) algorithm. …”
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An Intrusion Detection Model Based on Feature Selection and Improved One-Dimensional Convolutional Neural Network by Qingfeng Li, Bo Li, Linzhi Wen

“…Traditional machine learning techniques to intrusion detection rely on expert experience to choose features, and deep learning approaches have a low detection efficiency. …”
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UAV Mission Path Planning Based on Reinforcement Learning in Dynamic Environment by Gui Fu, Yang Gao, Liwen Liu, Mingye Yang, Xinyu Zhu

“…The path planning and optimization of UAV in dynamic environment is studied, and the path planning algorithm and Hungarian algorithm are added. The optimized UAV has the fastest data transmission and calculation speed, while the other two types of UAVs have slower data transmission and calculation speed. …”
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Data source and utilization of artificial intelligence technologies in vascular surgery—a scoping review by Katarzyna Powezka, Katarzyna Powezka, Katarzyna Powezka, Karin Slater, David Brind, Michael Wall, Michael Wall, Georgios Gkoutos, Maciej Juszczak, Maciej Juszczak

“…NLP algorithms were described in 34 papers, while 115 and 193 papers focused on machine learning (ML) and deep learning (DL), respectively. …”
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