Supervised Machine Learning Models for Predicting Sepsis-Associated Liver Injury in Patients With Sepsis: Development and Validation Study Based on a Multicenter Cohort Study by Jingchao Lei, Jia Zhai, Yao Zhang, Jing Qi, Chuanzheng Sun

“…Model performance was evaluated using accuracy, balanced accuracy, Brier score, detection prevalence, F1-score, Jaccard index, κ coefficient, Matthews correlation coefficient, negative predictive value, positive predictive value, precision, recall, area under the receiver operating characteristic curve (ROC-AUC), precision-recall AUC, and decision curve analysis. …”
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Content-Based Brain Magnetic Resonance Image Retrieval and Classification With the Proposed Deep Learning and Tissue-Based System by Bedriye Dogan, Hursit Burak Mutlu, Muhammed Yildirim, Sercan Yalcin, Serpil Aslan, Niranjana Sampathila, Ozal Yildirim, Edward J. Ciaccio, Ru-San Tan, U. Rajendra Acharya

“…A hybrid model was first devised to facilitate image retrieval by employing a pre-trained EfficientNet-b0 and local binary pattern (LBP) for feature extraction. These extracted features were then amalgamated to encompass diverse aspects of each image. …”
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Assessment of feasibility of actigraphy as a measure of clinical change in response to an experimental interventional treatment in adolescents and adults with autism spectrum disor... by Matthew Boice, Svetlana Bryant, Matthew Klein, Martine Meyer, Abi Bangerter, Srinivasan Vairavan, Gahan Pandina

“…Expert review was used to confirm validity of automated sleep/wake period detection. Feature differences were then assessed using t tests/ANCOVA. …”
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Large-Scale Monitoring of Potatoes Late Blight Using Multi-Source Time-Series Data and Google Earth Engine by Zelong Chi, Hong Chen, Sheng Chang, Zhao-Liang Li, Lingling Ma, Tongle Hu, Kaipeng Xu, Zhenjie Zhao

“…The feature importance analysis highlights key features for disease identification: the NIR band (B8) for Sentinel-2, DVI, SAVI, and the VH band for Sentinel-1. …”
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Ultrasound-based machine learning model to predict the risk of endometrial cancer among postmenopausal women by Yi-Xin Li, Yu Lu, Zhe-Ming Song, Yu-Ting Shen, Wen Lu, Min Ren

“…Conclusions This study demonstrates the feasibility and clinical value of AI-enhanced ultrasound analysis for EC detection. By integrating radiomics and deep learning features with SR-based image preprocessing, our model improves diagnostic specificity, reduces false positives, and mitigates operator-dependent variability. …”
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Identification of Ion-kinetic Instabilities in Hybrid-PIC Simulations of Solar Wind Plasma with Machine Learning by Viacheslav M. Sadykov, Leon Ofman, Scott A. Boardsen, Yogesh, Parisa Mostafavi, Lan K. Jian, Kristopher Klein, Mihailo Martinović

“…The addition of the E _⊥ power spectrum as an input for the ML models leads to the improvement of instability analysis for some cases. The results demonstrate the potential of ML and DL for the detection of ion-scale kinetic instabilities using spacecraft observations of SW and magnetospheric plasmas.…”
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The Role of Kidney Biopsy in Fabry Disease by Irene Capelli, Laura Martano, Gian Marco Berti, Gisella Vischini, Sarah Lerario, Vincenzo Donadio, Alex Incensi, Valeria Aiello, Francesca Ciurli, Benedetta Fabbrizio, Stefano Chilotti, Renzo Mignani, Gianandrea Pasquinelli, Gaetano La Manna

“…Renal involvement is a key feature, and kidney biopsy remains a valuable tool for diagnosing FD and assessing the extent of nephropathy. …”
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Preoperative DBT-based radiomics for predicting axillary lymph node metastasis in breast cancer: a multi-center study by Shuyan He, Biao Deng, Jiaqi Chen, Jiamin Li, Xuefeng Wang, Guanxing Li, Siyu Long, Jian Wan, Yan Zhang

“…We performed 3D region of interest (ROI) delineation on the cranio-caudal (CC) and mediolateral oblique (MLO) views of DBT images and extracted radiomic features. Using methods such as analysis of variance (ANOVA) and least absolute shrinkage and selection operator (LASSO), we selected radiomic features extracted from the tumor and its surrounding 3 mm, 5 mm, and 10 mm regions, and constructed a radiomic feature set. …”
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Factors of coxitis progression in patients with axial spondyloarthritis. Results of a two-year dynamic observation by E. M. Agafonova, Sh. Erdes, T. V. Dubinina, A. B. Demina, A. V. Smirnov

“…To detect the relationship between the clinical manifestations of axSpA and the radiographic progression of coxitis, a cluster analysis of the main parameters was performed.Results and discussion. …”
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FinSafeNet: securing digital transactions using optimized deep learning and multi-kernel PCA(MKPCA) with Nyström approximation by Ahmad Raza Khan, Shaik Shakeel Ahamad, Shailendra Mishra, Mohd Abdul Rahim Khan, Sunil Kumar Sharma, Abdullah AlEnizi, Osama Alfarraj, Majed Alowaidi, Manoj Kumar

“…Upon that, the model then applies the Multi-Kernel Principal Component Analysis (MKPCA) accompanied by Nyström Approximation for handling the MKPCA features. …”
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Differentiation of canine and feline neoplasms using multi-modal imaging and machine learning by Martynas Maciulevičius, Greta Rupšytė, Renaldas Raišutis, Blaž Cugmas, Mindaugas Tamošiūnas

“…The multimodal effect was obtained using both statistically significant set of features as well as optimal set of features, determined using sequential feature addition. …”
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Autoencoder untuk Sistem Prediksi Berat Lahir Bayi by Fitra Septia Nugraha, Hilman Ferdinandus Pardede

“…Teknik konvensional untuk feature reduction seperti principal component analysis (PCA), mengasumsikan orthogonality atau independensi antar komponen prinsipal nya. …”
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AxonFinder: Automated segmentation of tumor innervating neuronal fibers by Kaoutar Ait-Ahmad, Cigdem Ak, Guillaume Thibault, Young Hwan Chang, Sebnem Ece Eksi

“…Furthermore, our analysis includes a comprehensive assessment of axon density and morphological features across different CAPRA-S prostate cancer risk categories revealing a significant decline in axon density correlating with higher CAPRA-S prostate cancer risk scores. …”
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Multilingual person name recognition and transliteration by Bruno Pouliquen, Ralf Steinberger, Camelia Ignat, Irina Temnikova, Anna Widiger

“…This work is part of a news analysis system that clusters an average of 25,000 news articles per day to detect related news within the same and across different languages.…”
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An Investigation in Analyzing the Food Quality Well-Being for Lung Cancer Using Blockchain through CNN by Mohamed Abdelkader Aboamer, Mohamed Yacin Sikkandar, Sachin Gupta, Luis Vives, Kapil Joshi, Batyrkhan Omarov, Sitesh Kumar Singh

“…A greater pixel/resolution also improves the accuracy of cancer and food image detection. When images are provided with excellent features and filters, the CNN accuracy improves. …”
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A dual GAN with identity blocks and pancreas-inspired loss for renewable energy optimization by Mostafa Elbaz, Wael Said, Gamal M. Mahmoud, Hanaa Salem Marie

“…Abstract Integrating energy and solar imagery is essential for electrical engineers in renewable energy prediction, consumption analysis, regression modeling, and fault detection applications. …”
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Coal gangue image recognition model based on improved U−Net and top coal caving control by Yong YUAN, Zhenghan QIN, Yongqi XIA, Rang WU, Libao LI, Yong LI

“…An advanced U−Net−based coal gangue segmentation model has been developed, incorporating Feature Pyramid Networks (FPN) and Atrous Spatial Pyramid Pooling (ASPP). …”
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Hemoglobin state-flux: A finite-state model representation of the hemoglobin signal for evaluation of the resting state and the influence of disease. by Randall L Barbour, Harry L Graber, San-Lian S Barbour

“…Notable features of the methodology include access to this information solely from measures acquired in the resting state, and analysis of these by treating the various components of the hemoglobin (Hb) signal as a co-varying interacting system.…”
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Damage Identification Using Meta-Lens and Dual-Enhanced Backscattered Waves: Numerical and Experimental Design by Jiahui SHI, Gabriele Cazzulani, Claudio Sbarufatti

“… This paper introduces a Meta-lens designed for the detection of minute damage in Structural Health Monitoring (SHM) by amplifying backscattered waves originating from anomalous areas. …”
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Face Spoof Attack Recognition Using Discriminative Image Patches by Zahid Akhtar, Gian Luca Foresti

“…Though several face antispoofing or liveness detection methods (which determine at the time of capture whether a face is live or spoof) have been proposed, the issue is still unsolved due to difficulty in finding discriminative and computationally inexpensive features and methods for spoof attacks. …”
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