Leveraging BiLSTM-CRF and adversarial training for sentiment analysis in nature-based digital interventions: Enhancing mental well-being through MOOC platforms by Juanjuan Zang

“…This involves incorporating perturbations in the embedding space, generating adversarial samples at the embedding layer and semantic feature fusion layer, and combining these with the original samples for model training. …”
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Rapid Quality Discrimination of Rice during the Mildew Process Based on Multi-Source Information Fusion by LI Haiyu, WEI Ziyu, CHEN Tong, HUANG Guangwei, HU Yongzhi, MENG Hecheng

“…Based on total mold counts, rice became moldy on the 22th day. The model developed through feature variable fusion of GC-MS and FTIR data proved to be the most effective in differentiating the quality of rice at different stages of mildew, which was successfully clustered into 7 stages. …”
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Improved Value of Individual Prenatal Care for the Interdisciplinary Team by Ella Damiano, Regan Theiler

“…We sought to increase the value of traditional prenatal care by using a new model (PodCare) featuring a standardized visit schedule and coordination of care within small interdisciplinary teams in an academic setting. …”
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Securing IoT-Cloud Applications with AQ-KGMO-DMG Enhanced SVM for Intrusion Detection by Konduru Siva Naga Narasimharao, P. V. Lakshmi

“…The experimental findings showed that the proposed model performed better than conventional techniques in terms of FAR, accuracy, and computation cost. …”
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A New, Robust, Adaptive, Versatile, and Scalable Abandoned Object Detection Approach Based on DeepSORT Dynamic Prompts, and Customized LLM for Smart Video Surveillance by Merve Yilmazer, Mehmet Karakose

“…Then, human and object classes were detected using the weights of the YOLOv8l model, which has a fast and effective object detection feature. …”
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Trustworthy diagnosis of Electrocardiography signals based on out-of-distribution detection. by Bowen Yu, Yuhong Liu, Xin Wu, Jing Ren, Zhibin Zhao

“…However, these methods struggle with new or Out-of-Distribution (OOD) heart diseases. The deep learning model performs well on existing heart diseases but falters on unknown types, which leads to less reliable diagnoses. …”
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Evaluation of a Peak-Free Chemometric Laser-Induced Breakdown Spectroscopy Method for Direct Rapid Cancer Detection via Trace Metal Biomarkers in Tissue by Otieno Emily Akinyi, Angeyo Hudson Kalambuka, Alix Dehayem-Kamadjeu

“…In this work, a peak-free chemometric LIBS method based on a single-shot (for rapidity and nondestructiveness) and an artificial neural network multivariate calibration strategy with spectral feature selection was evaluated for its utility for direct trace quantitative analysis of copper (Cu), iron (Fe), manganese (Mg), magnesium (Mg), and zinc (Zn) in model soft body tissue. …”
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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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Predictive factors for the development of depression in children and adolescents: a clinical study by Hong Zhang, Peilin Yu, Xiaoming Liu, Xiaoming Liu, Ke Wang, Ke Wang, Ke Wang, Ke Wang

“…Independent risk factors were identified via univariate logistic regression analyses and least absolute shrinkage and selection operator (LASSO) for feature screening. Area under the curve (AUC) and decision curve analysis (DCA) were used to compare the predictive performance and clinical utility of these models. …”
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The Role of Artificial Intelligence in Predicting the Progression of Intraocular Hypertension to Glaucoma by Nicoleta Anton, Cătălin Lisa, Bogdan Doroftei, Ruxandra Angela Pîrvulescu, Ramona Ileana Barac, Ionuț Iulian Lungu, Camelia Margareta Bogdănici

“…The findings were compared with experimental data. The performance of the neural models was evaluated using several metrics: Mean Squared Error (MSE), Normalized Mean Squared Error (NMSE), correlation coefficient (r²), and percentage error (Ep). …”
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microRNA-1 regulates metabolic flexibility by programming adult skeletal muscle pyruvate metabolism by Ahmed Ismaeel, Bailey D. Peck, McLane M. Montgomery, Benjamin I. Burke, Jensen Goh, Abigail B. Franco, Qin Xia, Katarzyna Goljanek-Whysall, Brian McDonagh, Jared M. McLendon, Pieter J. Koopmans, Daniel Jacko, Kirill Schaaf, Wilhelm Bloch, Sebastian Gehlert, Kevin A. Murach, Kelsey H. Fisher–Wellman, Ryan L. Boudreau, Yuan Wen, John J. McCarthy

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EFFC-Net: lightweight fully convolutional neural networks in remote sensing disaster images by Jianye Yuan, Xin Ma, Zhentong Zhang, Qiang Xu, Ge Han, Song Li, Wei Gong, Fangyuan Liu, Xin Cai

“…Subsequently, EFFC-Net is compared with CNN and transformer models. Results show that the EFFC-Net network model performs effectively in precision, recall, F1_score, and parameters, outperforming the more advanced CNN and transformer models. …”
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Detecting soil mixing, grain size distribution, and clogging potential of tunnel excavation face by classification-regression algorithms using EPBM operational data by Sharmin Sarna, Marte Gutierrez

“…The results indicate successful prediction performances by the models, providing indication that EPBM parameters are crucial pointers of the tunnel excavation face properties to help attain optimally efficient EPBM operation.…”
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SEMSF-Net: Explainable Squeeze–Excitation Multiscale Fusion Network for Aerial Scene and Coastal Area Recognition Using Remote Sensing Images by Muhammad John Abbas, Muhammad Attique Khan, Ameer Hamza, Shrooq Alsenan, Areej Alasiry, Mehrez Marzougui, Yang Li, Yunyoung Nam

“…These blocks are designed based on the multiscale to generate more important feature information that can later perform accurate classification. …”
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3D computed tomography-dacryocystography (3D CT-DCG) and the contrast agents: direct comparison of Lipiodol and barium sulfate by Rafal Nowak, Izabela Nowak-Gospodarowicz, Aleksandra Kinga Kicinska, Marek Rękas, Maja Nowak, Mohammad Javed Ali

“…The analysis was performed in R, version 4.3.2. The overall mean volume of the dye (filling feature) in the 3D CTDCG reconstructed models of the lacrimal system following lipiodol injection was 55.2 mm3 vs. 244.2 mm3 with barium sulfate (p < 0.001). …”
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A Microscale Framework for Seismic Stability Analysis of Bridge Pier Rocking Isolation Using the Discrete Element Method by Idowu Itiola, Usama El Shamy

“…Validation was performed using well-documented experimental data featuring the free-rocking of a granite stone block as well as existing analytical techniques. …”
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Application of Optimal Control Theory to Newcastle Disease Dynamics in Village Chicken by Considering Wild Birds as Reservoir of Disease Virus by Furaha Chuma, Gasper Godson Mwanga, Verdiana Grace Masanja

“…A notable feature of this model is the inclusion of environment contamination and wild birds, which act as reservoirs of the disease virus. …”
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Allergen-specific circulating CLA+ memory T cells stratify IL-22 response in atopic dermatitis skin by Irene García-Jiménez, Irene García-Jiménez, Lídia Sans-de San Nicolàs, Sandra Díez-Ribas, Laia Curto-Barredo, Marta Bertolín-Colilla, Ana Vivancos-Melenchón, Ignasi Figueras-Nart, Montserrat Bonfill-Ortí, Anna Ryzhkova, Marta Ferran, Tali Czarnowicki, Ramon M. Pujol, Luis F. Santamaria-Babí

“…Additionally, we performed histological and gene expression analysis in lesional skin biopsies, assessed specific IgE levels in plasma, and together with the clinical features of the patients, were related to the IL-22 in vitro response.ResultsHDM triggered heterogeneous IL-22 secretion in memory T cells, preferentially in the CLA+ subset, which enabled patient stratification into IL22 producers (IL22P, n=17) and non-producers (IL22NP, n=41). …”
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SAMF-YOLO: A self-supervised, high-precision approach for defect detection in complex industrial environments. by Jun Huang, Shamsul Arrieya Ariffin, Qiang Zhu, Wanting Xu, Qun Yang

“…As object detection models grow in complexity, balancing computational efficiency and feature expressiveness becomes a critical challenge. …”
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MonoAMP: Adaptive Multi-Order Perceptual Aggregation for Monocular 3D Vehicle Detection by Xiaoxi Hu, Tao Chen, Wentao Zhang, Guangyi Ji, Hongxia Jia

“…However, existing methods face certain limitations in cross-dimensional feature attention mechanisms and multi-order contextual information modeling, which constrain their detection performance in complex scenes. …”
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