A Novel Bilateral Data Fusion Approach for EMG-Driven Deep Learning in Post-Stroke Paretic Gesture Recognition by Alexey Anastasiev, Hideki Kadone, Aiki Marushima, Hiroki Watanabe, Alexander Zaboronok, Shinya Watanabe, Akira Matsumura, Kenji Suzuki, Yuji Matsumaru, Hiroyuki Nishiyama, Eiichi Ishikawa

“…We introduce a hybrid deep learning model for recognizing hand gestures from electromyography (EMG) signals in subacute stroke patients: the one-dimensional convolutional long short-term memory neural network (CNN-LSTM). …”
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Enhancing Radiologist Productivity with Artificial Intelligence in Magnetic Resonance Imaging (MRI): A Narrative Review by Arun Nair, Wilson Ong, Aric Lee, Naomi Wenxin Leow, Andrew Makmur, Yong Han Ting, You Jun Lee, Shao Jin Ong, Jonathan Jiong Hao Tan, Naresh Kumar, James Thomas Patrick Decourcy Hallinan

“…A few studies also explored machine learning-based automation software and, more recently, large language models. Although most demonstrated gains in efficiency and accuracy, limited external validation and dataset heterogeneity could reduce broader adoption. …”
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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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Rapid estimation of DON content in wheat flour using close‐range hyperspectral imaging and machine learning by Dinesh Kumar Saini, Anshul Rana, Jyotirmoy Halder, Mohammad Maruf Billah, Harsimardeep S. Gill, Jinfeng Zhang, Subash Thapa, Shaukat Ali, Brent Turnipseed, Karl Glover, Maitiniyazi Maimaitijiang, Sunish K. Sehgal

“…Abstract Fusarium head blight (FHB) is one of the most destructive fungal diseases affecting wheat (Triticum aestivum). …”
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Large-Scale Apple Orchard Identification from Multi-Temporal Sentinel-2 Imagery by Chunxiao Wu, Yundan Liu, Jianyu Yang, Anjin Dai, Han Zhou, Kaixuan Tang, Yuxuan Zhang, Ruxin Wang, Binchuan Wei, Yifan Wang

“…Accurately extracting large-scale apple orchards from remote sensing imagery is of importance for orchard management. Most studies lack large-scale, high-resolution apple orchard maps due to sparse orchard distribution and similar crops, making mapping difficult. …”
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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

“…To interpret model decisions, gradient-weighted class activation mapping (Grad-CAM) was applied to visualize regions of the input images that contributed most to predictions, enabling identification of key prognostic features. …”
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Myoelectric signal and machine learning computing in gait pattern recognition for flat fall prediction by Shuo Zhang, Biao Chen, Chaoyang Chen, Maximillian Hovorka, Jin Qi, Jie Hu, Gui Yin, Marie Acosta, Ruby Bautista, Hussein F. Darwiche, Bryan E. Little, Carlos Palacio, John Hovorka

“…The accuracy was 67.39 % for LSTM and 74.75 % for BiLSTM, respectively. Most ML algorithms in this study had an accuracy greater than 90 ​% in EMG-based abnormal gait pattern recognition except for LSTM and BiLSTM. …”
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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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Traditional Chinese medicine diagnostic prediction model for holistic syndrome differentiation based on deep learning by Zhe Chen, Dong Zhang, Chunxiang Liu, Hui Wang, Xinyao Jin, Fengwen Yang, Junhua Zhang

“…Based on the Bidirectional Encoder Representations from Transformers (BERT) and Convolutional Neural Networks (CNN) models, with the classification constraints from TCM holistic syndrome differentiation, the TCM-BERT-CNN model was constructed, which completes the end-to-end TCM holistic syndrome text classification task through symptom input and syndrome output. …”
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Artificial Intelligence in Pediatric Orthopedics: A Comprehensive Review by Andrea Vescio, Gianluca Testa, Marco Sapienza, Filippo Familiari, Michele Mercurio, Giorgio Gasparini, Sergio de Salvatore, Fabrizio Donati, Federico Canavese, Vito Pavone

“…Bone age estimation using DL models often matched or outperformed traditional methods. However, most studies lacked external validation, and many relied on small or single-institution datasets. …”
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Leveraging Machine Learning and Remote Sensing for Water Quality Analysis in Lake Ranco, Southern Chile by Lien Rodríguez-López, Lisandra Bravo Alvarez, Iongel Duran-Llacer, David E. Ruíz-Guirola, Samuel Montejo-Sánchez, Rebeca Martínez-Retureta, Ernesto López-Morales, Luc Bourrel, Frédéric Frappart, Roberto Urrutia

“…Among these models, LSTM stands out as the most effective, with the best metrics in the estimation, the best performance was Case 1, with R² = 0.89, an RSME of 0.32 µg/L, an MAE 1.25 µg/L and an MSE 0.25 (µg/L)², consistently outperforming the others according to the static metrics used for validation. …”
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VdaBSC: A Novel Vulnerability Detection Approach for Blockchain Smart Contract by Dynamic Analysis by Rexford Nii Ayitey Sosu, Jinfu Chen, Edward Kwadwo Boahen, Zikang Zhang

“…Methods currently used for identifying vulnerabilities in smart contracts mostly rely on static analysis methods that search for predefined vulnerability patterns. …”
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Multimodal fusion based few-shot network intrusion detection system by Congyuan Xu, Yong Zhan, Zhiqiang Wang, Jun Yang

“…Existing few-shot learning methods, while reducing reliance on large datasets, mostly handle single-modality data and fail to fully exploit complementary information across different modalities, limiting detection performance. …”
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Multi-stage framework using transformer models, feature fusion and ensemble learning for enhancing eye disease classification by Abdulaziz AlMohimeed

“…However, current methods mostly use single-model architectures, including convolutional neural networks (CNNs), which might not adequately capture the long-range spatial correlations and local fine-grained features required for classification. …”
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A Deep Reinforcement Learning Approach for Portfolio Management in Non-Short-Selling Market by Ruidan Su, Chun Chi, Shikui Tu, Lei Xu

“…Reinforcement learning (RL) has been applied to financial portfolio management in recent years. Current studies mostly focus on profit accumulation without much consideration of risk. …”
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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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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

“…Therefore, in order to regulate the negative pressure of gas extraction system reasonably and accurately, four prediction algorithms are compared and analyzed, and the most excellent prediction algorithm is selected and improved according to its own shortcomings. …”
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Category semantic and global relation distillation for object detection by Yanpeng LIANG, Zhonggui MA, Zongjie WANG, Zhuo LI

“…Knowledge distillation stands out as it transfers knowledge from large teacher models to compact student models without modifying the network structure, enabling the student models to perform nearly as well as their larger counterparts. However, most distillation techniques have been optimized for image classification, not object detection, which involves simultaneously detecting and classifying multiple target objects within natural images. …”
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