Epidemiology and management of atopic dermatitis in England: an observational cohort study protocol by Simon de Lusignan, Carsten Flohr, John Dennis, Helen Alexander, Conor Broderick, Andrew McGovern, Claire Feeney

“…Regarding healthcare utilisation, we will evaluate rates of AD-associated primary care visits and specialist dermatology referrals in people with AD. …”
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Assessing the effects of therapeutic combinations on SARS-CoV-2 infected patient outcomes: A big data approach. by Hamidreza Moradi, H Timothy Bunnell, Bradley S Price, Maryam Khodaverdi, Michael T Vest, James Z Porterfield, Alfred J Anzalone, Susan L Santangelo, Wesley Kimble, Jeremy Harper, William B Hillegass, Sally L Hodder, National COVID Cohort Collaborative (N3C) Consortium

“…The approach also provides a framework for simultaneously evaluating multiple real-world therapeutic combinations in future research studies.…”
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TransformerPayne: Enhancing Spectral Emulation Accuracy and Data Efficiency by Capturing Long-range Correlations by Tomasz Różański, Yuan-Sen Ting, Maja Jabłońska

“…While scaling up The Payne to a larger network reduced its MAE from 1.2% to 0.3% when trained on the full data set, TransformerPayne consistently achieved the lowest MAE across all tests. …”
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Development of a hip osteoarthritis index for gait quality assessment: a data-driven comparative study by Kamyar Rahmani, Mansour Davoudi, Mohammad Sajjad Alamdar, Rezvan Nasiri

“…Additionally, we employed multi-layer perceptron (MLP) and deep recurrent neural network (RNN) models to evaluate the efficacy of our linear model. …”
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Segmentation-Assisted Fusion-Based Classification for Automated CXR Image Analysis by Shilu Kang, Dongfang Li, Jiaxin Xu, Aokun Mei, Hua Huo

“…The method involves two stages: first, we use a lightweight segmentation model, Partial Convolutional Segmentation Network (PCSNet) designed based on an encoder–decoder architecture, to accurately obtain lung masks from CXR images. …”
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AppAuth: Authorship Attribution for Android App Clones by Guoai Xu, Chengpeng Zhang, Bowen Sun, Xinyu Yang, Yanhui Guo, Chengze Li, Haoyu Wang

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Estimating chlorophyll content in tea leaves using spectral reflectance and deep learning methods by Yuta Tsuchiya, Yuhei Hirono, Rei Sonobe

“…Accurate estimation of chlorophyll content in tea leaves is essential for evaluating plant health, managing fertilization, and optimizing harvest timing in precision agriculture. …”
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Machine learning predictive performance in road accident severity: A case study from Thailand by Ittirit Mohamad, Sajjakaj JomnonKwao, Vatanavongs Ratanavaraha

“…Future work should explore advanced feature engineering and ensemble techniques to enhance fatality prediction accuracy.…”
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Eeg-based detection of epileptic seizures in patients with disabilities using a novel attention-driven deep learning framework with SHAP interpretability by Tawfeeq Shawly, Ahmed A. Alsheikhy

“…In this research, we introduce a cutting-edge deep learning methodology for the automated prediction of epilepsy, incorporating a Novel Attention Module (NAM) into a new Convolutional Neural Network (CNN) to improve the extraction of features from EEG signals. …”
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Machine learning-based prediction model for post-stroke cerebral-cardiac syndrome: a risk stratification study by Tingyu Zhang, Zelin Hao, Qunlian Jiang, Linhui Zhu, Lifang Ye

“…Five machine learning models, including Logistic Regression, Random Forest, Support Vector Machine (SVM), XGBoost, and Deep Neural Network, were trained on 80% of the data and tested on the remaining 20%. …”
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Potato precision planter metering system based on improved YOLOv5n-ByteTrack by Cisen Xiao, Changlin Song, Junmin Li, Min Liao, Yongfan Pu, Kun Du

“…Subsequently, re-parameterized convolution (RepConv) is incorporated into the feature extraction network architecture, enhancing the model’s inference speed by leveraging the correlation between features. …”
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A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis by Basma Jumaa Saleh, Zaid Omar, Muhammad Amir As’ari, Vikrant Bhateja, Lila Iznita Izhar

“…To address this, we propose an efficient, modified radiomics feature processing method that integrates an optimal aerial perspective (OAP) parameter-based intensity dark channel prior (IDCP) with a 50-layer residual deep neural network (ResNet50 DNN) for autolesion segmentation (ALS-IOAP-DNN). …”
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Multimodal Model for Automated Pain Assessment: Leveraging Video and fNIRS by Jo Vianto, Anjitha Divakaran, Hyungjeong Yang, Soonja Yeom, Seungwon Kim, Soohyung Kim, Jieun Shin

“…Our model leverages video and fNIRS modalities as well as manually extracted statistical features. We also implemented fNIRS signal preprocessing and artifact noise filtering, which significantly improved performance on both the fNIRS and statistical feature branches. …”
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Enhanced prediction of ventilator-associated pneumonia in patients with traumatic brain injury using advanced machine learning techniques by Negin Ashrafi, Armin Abdollahi, Kamiar Alaei, Maryam Pishgar

“…An ablation study validated the necessity of each retained feature, indicating that any feature removal led to a decline in model performance. …”
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Fatty acid metabolism influences the immune microenvironment in papillary thyroid cancer and identifies SCD as a novel biomarker by Bingbing Shen, Yu Zhang, Yan Tie

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Remote Sensing Image Compression via Wavelet-Guided Local Structure Decoupling and Channel–Spatial State Modeling by Jiahui Liu, Lili Zhang, Xianjun Wang

“…To address these issues, we present an innovative architecture for distant sensing image compression, called the Multi-scale Channel Global Mamba Network (MGMNet). MGMNet integrates a spatial–channel dynamic weighting mechanism into the Mamba architecture, enhancing global semantic modeling while selectively emphasizing informative features. …”
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Cost-Efficient Fall Risk Assessment With Attention Augmented Vision Machine Learning on Sit-to-Stand Test Videos by Chunhua Pan, Boting Qu, Rui Miao, Xin Wang

“…Furthermore, a novel Attention-augmented Spatial-Temporal Graph Convolutional Network (AST-GCN) is developed for reliably identifying the action in each frame, enabling accurate computation of key kinematic features for fall risk prediction. …”
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An artificial intelligence platform for predicting postoperative complications in metastatic spinal surgery: development and validation study by Weihao Jiang, Juan Zhang, Weiqing Shi, Xuyong Cao, Xiongwei Zhao, Bin Zhang, Haikuan Yu, Shengjie Wang, Yong Qin, Mingxing Lei, Yuncen Cao, Boyu Zhu, Yaosheng Liu

“…The machine learning algorithms employed in this study includes logistic regression (LR), decision tree (DT), random forest (RF), extreme gradient boosting machine (eXGBM), neural network (NN), and k-nearest neighbor (KNN). The evaluation metrics focused on both discrimination and calibration to ensure robust model’s prediction performance. …”
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Postresuscitative Morphofunctional Changes in the Brain and Retina (Experimental Study) by D. A. Yenikeyev, Ye. A. Nurgaleyeva, L. T. Idrisova, A. F. Samigullina, R. M. Gubaidullin, O. V. Laptev

“…The microcirculatory retinal circulatory disorders featured the staging of the course: vasodilatation and decreased capillary network density within the first 24 hours after resuscitation, followed by a progressive increase in the density of the capillary network from day 14, as compared with the control, and capillary diameter normalization. …”
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Machine learning-based integration identifies plasma cells-related gene signature ST6GAL1 in idiopathic pulmonary fibrosis by Fanjie Lin, Ken Lin, Donglei Li, Weiguo Kong, Jiayu Zhuang, Wei He, Xinguang Wei, Tianchi Xiao, Hao Zu, Zili Zhang, Wenju Lu

“…A core gene in the PCRGS was further identified and validated through experiments. Finally, the network pharmacology analysis for the core gene was implemented. …”
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