Machine Learning in Baseball Analytics: Sabermetrics and Beyond by Wenbing Zhao, Vyaghri Seetharamayya Akella, Shunkun Yang, Xiong Luo

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Left ventricle strain and T1 mapping evaluation in a mouse model with myocardial infarction by Khaoula Bouazizi, Thulaciga Yoganathan, Frank Kober, Gwennhael Autret, Perrine Marsac, Clément Delacroix, Shannon Soulez, Mohamed Zarai, Vincent Nguyen, Adil Squalli, Paul Alayrac, Estelle Robidel, Bertrand Tavitian, Alban Redheuil, Jean-Sébastien Hulot, Nadjia Kachenoura

“…The aim of this study is to provide normative myocardial strain and T1 values in mice model along with their changes after myocardial infarction (MI) using a tailored acquisition and analysis protocol. …”
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Bone filler and adhesive at the same time: in-vitro analysis in a porcine fracture model by Stefanie Hoelscher-Doht, Nicola Zufall, Maximilian Heilig, Philipp Heilig, Martin Cornelius Jordan, Rainer Heribert Meffert, Uwe Gbureck, Lea Hüls

“…The adhesive and drillable magnesium phosphate cement proved to be a versatile solution featuring a new surgical method in which the fracture was anatomically reduced using only the cement. …”
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Interpretable noninvasive diagnosis of tuberculous pleural effusion using LGBM and SHAP: development and clinical application of a machine learning model by Bihua Yao, Xingyu Yu, Liannv Qiu, Er-min Gu, Siyu Mao, Lei Jiang, Jijun Tong, Jianguo Wu

“…Light gradient boosting machine (LGBM) emerged as the top-performing model. Shapley Additive exPlanations (SHAP) analysis assessed feature importance and interpretability. …”
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Identifying the effectiveness of face mask in a large population with a network-based fluid model. by Akshay Anand, Kourosh Shoele

“…In this study, a new semi-analytical flow network model based on the Kármán-Pohlhausen technique is introduced and utilized to efficiently assess mask performance across diverse facial features that represent the observed variations inside a large population. …”
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Evaluating oxidative stress targeting treatments in in vitro models of placental stress relevant to preeclampsia by Dinara Afrose, Matt D. Johansen, Matt D. Johansen, Valentina Nikolic, Natasa Karadzov Orlic, Natasa Karadzov Orlic, Zeljko Mikovic, Zeljko Mikovic, Milan Stefanovic, Milan Stefanovic, Zoran Cakic, Philip M. Hansbro, Philip M. Hansbro, Lana McClements, Lana McClements

“…Placental dysfunction is a hallmark feature of preeclampsia, which is often caused by inappropriate trophoblast cell function in association with oxidative stress, inflammation and/or pathological hypoxia. …”
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Towards a global spatial machine learning model for seasonal groundwater level predictions in Germany by S. Kunz, A. Schulz, M. Wetzel, M. Nölscher, T. Chiaburu, F. Biessmann, S. Broda

“…To determine the conditions under which the model achieves good performance and whether it aligns with hydrogeological system understanding, the model's performance was evaluated spatially and correlations with both static input features and time series features from hydrograph data were examined.…”
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Enhanced Cloud Detection Using a Unified Multimodal Data Fusion Approach in Remote Images by Yan Mo, Puhui Chen, Wanting Zhou, Wei Chen

“…To address the challenge of unified multimodal feature extraction, we adopt two key strategies: (1) constructing feature extraction modules with shared but independent weights for each modality to preserve the inherent features of each modality; (2) utilizing cosine similarity to adaptively learn complementary features between different modalities, thereby reducing redundant information. …”
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A Novel Pseudo-Siamese Fusion Network for Enhancing Semantic Segmentation of Building Areas in Synthetic Aperture Radar Images by Mengguang Liao, Longcheng Huang, Shaoning Li

“…Finally, the model was optimized using the combined CE-Dice loss function to achieve superior performance. …”
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Multipath and Deep Learning-Based Detection of Ultra-Low Moving Targets Above the Sea by Zhaolong Wang, Xiaokuan Zhang, Weike Feng, Binfeng Zong, Tong Wang, Cheng Qi, Xixi Chen

“…Without suppressing interferences, the proposed method uses both target and multipath information for detection based on their distinguishable image features and deep learning (DL) techniques. First, the image features of the target, multipath, and sea clutter in the real-measured range-Doppler (RD) map are analyzed, based on which the target and multipath are defined together as the generalized target. …”
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Enhancing diabetes risk prediction: A comparative evaluation of bagging, boosting, and ensemble classifiers with SMOTE oversampling by Rabia Asif, Darshana Upadhyay, Marzia Zaman, Srini Sampalli

“…We find that applying SMOTE to the CDC dataset significantly enhances model performance, with the CATBoost algorithm achieving an accuracy of 91 %. …”
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Collaborative Superpixelwised PCA for Hyperspectral Image Classification by Chao Yao, Junrui Gu, Zehua Guo, Miao Ma, Qingrui Guo, Gong Cheng

“…A recently developed superpixelwised principal component analysis (PCA) (SuperPCA), which has shown its promising performance, is a prominent technique in spectral–spatial feature extraction. …”
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Performance prediction and optimization of a high-efficiency tessellated diamond fractal MIMO antenna for terahertz 6G communication using machine learning approaches by Kamal Hossain Nahin, Jamal Hossain Nirob, Akil Ahmad Taki, Md Ashraful Haque, Narinderjit Singh Sawaran Singh, Liton Chandra Paul, Reem Ibrahim Alkanhel, Hanaa A. Abdallah, Abdelhamied A. Ateya, Ahmed A. Abd El-Latif

“…The design methodology integrates CST simulations and an RLC equivalent circuit model, substantiated by ADS simulations, with comparable reflection coefficients validating the accuracy of the models. …”
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Video watermarking algorithm for resisting collusion attacks by LIU Shao-hui, HAN Lu, YAO Hong-xun

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Development, validation, and updating of prognostic models for m7G-associated genes from TAMs in lower-grade gliomas by Lei Ao, Huijun Li, Ke Zhang, Mengjie Li, Huan Liu, Zaixiang Tang

“…Based on CGGA information, updated models that were created matched the features of the local population. …”
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Assessing thermal and hydrodynamic performance of non-Newtonian nano-coolant flow through a porous backward-facing step channel with non-Darcian effects by Zarin Akter, Preetom Nag, Hasina Akter, Md. Mamun Molla, Goutam Saha

“…The study also evaluates the thermal performance criterion (PEC), which increases with higher Re but decreases with ϕ. …”
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T_SRNET: A multimodal model based on convolutional neural network for emotional speech enhancement by Shaoqiang Wang, Lei Feng, Li Zhang

“…However, the lack of high-quality speech annotation datasets makes it difficult for many models to provide sufficient data for training, resulting in poor model generalization performance. …”
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AMDCnet: attention-gate-based multi-scale decomposition and collaboration network for long-term time series forecasting by Shikang Hou, Song Sun, Tao Yin, Zhibin Zhang, Meng Yan

“…By extracting features from downsampled sequences and integrating multi-resolution features through attention-gated co-training mechanisms, AMDCnet enables efficient modeling of complex time series data.ResultsAMDCnet achieving 44 best results and 10 second-best results out of 64 cases. …”
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Improved machine learning framework for prediction of phases and crystal structures of high entropy alloys by Debsundar Dey, Suchandan Das, Anik Pal, Santanu Dey, Chandan Kumar Raul, Pritam Mandal, Arghya Chatterjee, Soumya Chatterjee, Manojit Ghosh

“…Various hyperparameter tuning was conducted to find the optimum performance of the boosting classifiers. A comprehensive comparison was performed between the ML models and some from published papers in reputed journals. …”
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SF-DETR: A Scale-Frequency Detection Transformer for Drone-View Object Detection by Haotong Wang, Junwei Gao

“…SF-DETR introduces a lightweight ScaleFormerNet backbone with Dual Scale Vision Transformer modules, a Bilateral Interactive Feature Enhancement Module, and a Multi-Scale Frequency-Fused Feature Enhancement Network. …”
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