Semantic classification of Indonesian consumer health questions by Raniah Nur Hanami, Rahmad Mahendra, Alfan Farizki Wicaksono

“…This framework facilitates a deeper understanding of the role played by word-based features in the model’s decision-making process. Additionally, it empowers us to conduct a comprehensive bias analysis, allowing for the detection of “semantic bias”, where words with no inherent association with a specific semantic type disproportionately influence the model’s predictions. …”
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NEW TYPE OF ELASTIC ROTATIONAL WAVES IN GEO-MEDIUM AND VORTEX GEODYNAMICS by Alexander V. Vikulin

“…Helmgolz, Lord Kelvin and others within the framework of classical physics and in the first half of the 20th century by scientists in quantum physics and cosmogony, both «quantum structure» («lumpiness») and rotation («vorticity») are integral features of matter – space – time throughout the whole range from elementary particles to galaxies and galactic clusters.Nowadays researchers in natural sciences, particularly in the Earth sciences, call attention again to the problem of structure of matter and its movements. …”
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Improving the Performance of Heart Disease Diagnosis by Combining the Cochleogram Transformation and Variable Auto-Encoder (VAE) Network by Mahbubeh Bahrayni, Ramin Barati, Abbas Kamali

“…This abnormal sound detection system can be used very usefully in rural health centers and small hospitals to help doctors without expertise to diagnose heart problems.…”
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Integrated model for segmentation of glomeruli in kidney images by Gurjinder Kaur, Meenu Garg, Sheifali Gupta

“…Kidney diseases, especially those that affect the glomeruli, have become more common worldwide in recent years. Accurate and early detection of glomeruli is critical for accurately diagnosing kidney problems and determining the most effective treatment options. …”
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Emergence of scrub typhus-associated neurological signs in central India: An unusual manifestation in febrile illness cases in Madhya Pradesh, India by Gayatri Sondhiya, Prakash Tiwari, HV Manjunathachar, Vivek Chouksey, Pradeep Tiwari, Pradip V. Barde, Chandrashekhar G. Raut, Tapas Chakma, Harpreet Kaur, Pushpendra Singh

“…Problem considered: Scrub typhus, a re-emerging zoonotic infection, often manifests as acute undifferentiated febrile illness (AUF), posing a significant epidemiological threat in tropical and subtropical regions. …”
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Mapping Invasive <italic>Spartina alterniflora</italic> Using Phenological Information and Red-Edge Bands of Sentinel-2 Time-Series Data by Yiwei Ma, Li Zhuo, Jingjing Cao

“…Since the phenological information and red-edge spectral differences have been considered as informative features for identifying <italic>S. alterniflora</italic>, current studies mainly used them separately as classification features and seldom considered the differences of red-edge information at different phenological periods. …”
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CrossModalSync: joint temporal-spatial fusion for semantic scene segmentation in large-scale scenes by Shuyi Tan, Yi Zhang, Yan Li, Byeong-Seok Shin

“…By combining TA and PMC, the framework effectively captures inter-frame correlations, improving local detail information, reducing error accumulation, and maintaining detailed scene features. Second, employing the PPR mechanism ensures that critical three-dimensional information is retained, thereby resolving information loss caused by the “many-to-one” mapping problem. …”
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Defect Diagnosis of Photovoltaic Module Visible Light Images Under Imbalanced Sample Conditions by Huiqing Rao, Qiong Li, Long Chen, Sha Jin, Yong Lu, Zhiguang Li

“…To address the issues of high miss and false detection rates in defect detection of PV (photovoltaic) module visible light images under imbalanced data conditions, an improved data augmentation method based on DCGAN (Deep Convolutional Generative Adversarial Networks) is proposed. …”
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Fault Identi fication of Rolling Bearing Based on Adaptive Wavelet Analysis and Multiple Layers Convolution Extreme Learning Auto-encoder by Yahong TAN

“…Aiming at the problems of rolling bearing vibration signals were dif ficult to identify due to strong time-varying and strong noisy characteristics, a method based on adaptive wavelet analysis (AWA) and multiple layers convolution extreme learning auto-encoder (MLCELAE) was proposed. …”
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Random Oversampling-Based Diabetes Classification via Machine Learning Algorithms by G. R. Ashisha, X. Anitha Mary, E. Grace Mary Kanaga, J. Andrew, R. Jennifer Eunice

“…The proposed model consists of the random oversampling method to balance the range of classes, the interquartile range technique-based outlier detection to eliminate outlier data, and the Boruta algorithm for selecting the optimal features from the datasets. …”
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Analysis of printed document identification based on Deep Learning by Dinh Thong Nguyen, Phu Quang Nguyen, Hoang Bao An Mai

“… In this study, we investigate the effectiveness of ResNet, a deep neural network architecture, for a deep learning approach to address the problem of printed document identification. ResNet is known for its ability to handle the vanishing gradient problem and learn highly representative features. …”
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Analysis of printed document identification based on Deep Learning by Dinh Thong Nguyen, Phu Quang Nguyen, Hoang Bao An Mai

“… In this study, we investigate the effectiveness of ResNet, a deep neural network architecture, for a deep learning approach to address the problem of printed document identification. ResNet is known for its ability to handle the vanishing gradient problem and learn highly representative features. …”
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A Computational Methodology Based on Maximum Overlap Discrete Wavelet Transform and Autoencoders for Early Prediction of Sudden Cardiac Death by Manuel A. Centeno-Bautista, Andrea V. Perez-Sanchez, Juan P. Amezquita-Sanchez, David Camarena-Martinez, Martin Valtierra-Rodriguez

“…The proposed method efficiently predicts an SCD event with an accuracy of 98.94% up to 30 min before the onset, making it a reliable tool for early detection while providing sufficient time for medical intervention and increasing the chances of preventing fatal outcomes, demonstrating the potential of integrating signal processing and deep learning techniques within computational biology to address life-critical health problems.…”
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Radiomics-driven neuro-fuzzy framework for rule generation to enhance explainability in MRI-based brain tumor segmentation by Leondry Mayeta-Revilla, Leondry Mayeta-Revilla, Leondry Mayeta-Revilla, Leondry Mayeta-Revilla, Eduardo P. Cavieres, Eduardo P. Cavieres, Eduardo P. Cavieres, Matías Salinas, Matías Salinas, Matías Salinas, Diego Mellado, Diego Mellado, Diego Mellado, Diego Mellado, Sebastian Ponce, Sebastian Ponce, Sebastian Ponce, Sebastian Ponce, Francisco Torres Moyano, Francisco Torres Moyano, Francisco Torres Moyano, Francisco Torres Moyano, Steren Chabert, Steren Chabert, Steren Chabert, Marvin Querales, Marvin Querales, Julio Sotelo, Rodrigo Salas, Rodrigo Salas, Rodrigo Salas

“…Although Deep Learning (DL) models offer strong performance in tumor detection and segmentation using MRI, their black-box nature hinders clinical adoption due to a lack of interpretability.MethodsWe present a hybrid AI framework that integrates a 3D U-Net Convolutional Neural Network for MRI-based tumor segmentation with radiomic feature extraction. …”
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Digital fundus image quality assessment by V. V. Starovoitov, Y. I. Golub, M. M. Lukashevich

“…On these images one can see features, which determine the presence of DR and its grade. …”
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Mopidip: a modular real-time pipeline for machinery diagnosis and prognosis based on deep learning algorithms by Mattia Pujatti, Davide Calzà, Andrea Gobbi, Piergiorgio Svaizer, Marco Cristoforetti

“…In the age of the digital industry, Artificial Intelligence (AI)-based data-driven condition monitoring is proving extremely effective in detecting potential issues before they escalate into major problems, thereby reducing downtime, minimizing maintenance costs, and extending the lifespan of the equipment. …”
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Optimizing of Universal DEA Model with Multi-Level Integration under Neutrosophic Environment by Hamiden Abd El- Wahed Khalifa, Loay Alkhalifa, Sultan S. Alodhaibi, Basma E. El- Demerdash

“…This research introduces a comprehensive Universal Data Envelopment Analysis (DEA) model to handle real-world problems fraught with uncertainty of every operational facet. …”
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Steganalysis Using KL Transform and Radial Basis Neural Network by Safwan Hasoon, Farhad Khalifa

“…The essential problem in the security field is how to detect information hiding. …”
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PROMOTER REGION rs1800629 TNFα POLYMORPHISM AND ITS INFLUENCE ON TUMOR NECROSIS FACTOR ALPHA CONCENTRATION IN BLOOD OF HEALTHY INDIVIDUALS AND PATIENTS WITH ERYSIPELAS by A. S. Emelyanov, A. N. Emelyanova, B. S. Pushkarev, Yu. A. Vitkovsky

“…The prediction of the course of erysipelas is unresolved problem yet. The genetic features of the organism, such as the genetic polymorphisms of some cytokines, involved on the prediction of the course of erysipelas. …”
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A Multimodel Decision Fusion Method Based on DCNN-IDST for Fault Diagnosis of Rolling Bearing by Weixiao Xu, Luyang Jing, Jiwen Tan, Lianchen Dou

“…The DCNN model can learn features from the original data and carry out adaptive feature extraction for multiple sensor information. …”
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