Quantitative response assessment of combined immunotherapy in a murine melanoma model using multiparametric MRI by Maurice M. Heimer, Amra Cimic, Sandra Kloiber-Langhorst, Melissa J. Antons, Jennifer Stueckl, Heidrun Hirner-Eppeneder, Wolfgang G. Kunz, Olaf Dietrich, Jens Ricke, Felix L. Herr, Clemens C. Cyran

“…Abstract Background We assessed immunotherapy response in a murine melanoma model using multiparametric magnetic resonance imaging (mpMRI) features with ex vivo immunohistochemical validation. …”
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Inductive and Transfer Learning‐Based Hybrid Model Techniques for Accurate and Automated Diagnosis of Neurological Diseases by Saroj Kumar Pandey, Yogesh Kumar Rathore, Sunakshi Mehra, Anurag Sinha, Tarun Raj Kumar, Ankit Kumar, Rekh Ram Janghel, Ayodele Lasisi, Quadri Noorulhasan Naveed, Md. Sazid Reza

“…It addresses key limitations of existing CAD systems by providing a unified, dual‐disease diagnosis model with statistically validated performance gains. …”
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YOLOv8-RBean: Runner Bean Leaf Disease Detection Model Based on YOLOv8 by Hongbing Chen, Haoting Zhai, Jinghuan Hu, Hongrui Chen, Changji Wen, Yizhe Feng, Kun Wang, Zhipeng Li, Guangyao Wang

“…The model enhances detection performance through three key innovations: (1) the BeanConv module, which integrates depthwise separable convolution and pointwise convolution to improve multi-scale feature extraction; (2) a lightweight LA attention mechanism that incorporates spatial, channel, and coordinate information to enhance feature representation; and (3) a lightweight BLBlock structure built upon DWConv and LA attention, which optimizes computational efficiency while maintaining high accuracy. …”
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Inversion Model for Total Nitrogen in Rhizosphere Soil of Silage Corn Based on UAV Multispectral Imagery by Hongyan Yang, Jixuan Yan, Guang Li, Weiwei Ma, Xiangdong Yao, Jie Li, Qihong Da, Xuchun Li, Kejing Cheng

“…Among the nitrogen inversion models based on different machine learning algorithms, the PLSR model showed the best performance, followed by the RF model, while the BPNN model performed the worst. …”
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Predictive analytics of complex healthcare systems using deep learning based disease diagnosis model by Muhammad Kashif Saeed, Alanoud Al Mazroa, Bandar M. Alghamdi, Fouad Shoie Alallah, Abdulrhman Alshareef, Ahmed Mahmud

“…The simulation values of the PACHS-DLBDDM approach are examined on a medical image dataset. The performance validation of the PACHS-DLBDDM model portrays the superior accuracy value of 99.54% over other DL models.…”
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Predicting the Compression Index of Clayey Soils Using a Hybrid Genetic Programming and XGBoost Model by Abolfazl Baghbani, Katayoon Kiany, Hossam Abuel-Naga, Yi Lu

“…The hybrid GP-XGBoost model achieved remarkable predictive performance, with an <i>R</i>² of 0.966 and 0.927 and mean squared error (MSE) values of 0.001 and 0.001 for training and testing datasets, respectively. …”
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AUTOMATIC SCORING OF KNOWLEDGE GAINED AND SHARED THROUGH DISCUSSION FORUMS: BASED ON THE COMMUNITY OF INQUIRY MODEL by P.A.L. Nadeesha, T.A. Weerasinghe, W.R.N.S Abeyweera

“…This highlights the robustness of the combined approach in enhancing classification performance. Furthermore, the study introduces a scoring model that calculates individual student scores based on post categories, enabling detailed evaluations of student engagement and participation. …”
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YOLO-FDCL: Improved YOLOv8 for Driver Fatigue Detection in Complex Lighting Conditions by Genchao Liu, Kun Wu, Wei Lan, Yunjie Wu

“…Additionally, by incorporating the concept of structural re-parameterization, RepFPN is introduced into the neck section of the algorithm to strengthen the network’s multi-scale feature fusion capabilities, further improving the model’s detection performance. …”
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Deep and Shallow Learning Model-Based Sleep Apnea Diagnosis Systems: A Comprehensive Study by Roksana Akter Raisa, Ayesha Siddika Rodela, Mohammad Abu Yousuf, Akm Azad, Salem A. Alyami, Pietro Lio, Md Zahidul Islam, Ganna Pogrebna, Mohammad Ali Moni

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Explainable machine learning model for predicting the transarterial chemoembolization response and subtypes of hepatocellular carcinoma patients by Yunjie Zhang, Songjian Tong, Junhui Yang, Jiawei Lin, Yifan Kong, Deyu Lu, Yan Chen, Yingchao Li, Linfeng Xu, Xiuyan Kong, Guoqing Zhu, Hao Zhang, Pixu Liu, Zhijie Yu, Jinglin Xia

“…The SHAP algorithm was implemented to enhance model interpretability, while patient stratification was subsequently performed using PCA and K-means clustering to facilitate comprehensive prognostic analysis. …”
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Fetal Birth Weight Prediction in the Third Trimester: Retrospective Cohort Study and Development of an Ensemble Model by Jing Gao, Xu Jie, Yujun Yao, Jingdong Xue, Lei Chen, Ruiyao Chen, Jiayuan Chen, Weiwei Cheng

“…In addition, our model maintained superior performance for low birth weight and macrosomic fetal populations. …”
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Deep Learning and Methods Based on Large Language Models Applied to Stellar Light Curve Classification by Yu-Yang Li, Yu Bai, Cunshi Wang, Mengwei Qu, Ziteng Lu, Roberto Soria, Jifeng Liu

“…Remarkably, StarWhisper LC series models exhibit high accuracies of around 90%, considerably reducing the need for explicit feature engineering, thereby paving the way for streamlined parallel data processing and the progression of multifaceted multimodal models in astronomical applications. …”
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Model Test Study on Dynamic Response of Expressway Plastic-Reinforced Earth Embankment under Earthquake by Xue Han, Pengyue Ji, Qichen Gu, Guangsen Mu

“…The peak dynamic soil pressure of the unreinforced embankment at the same location was significantly greater than that of the reinforced embankment. The two embankment models showed significantly different antivibration damage performance. …”
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Novel integrative models to predict the severity of inflammation and fibrosis in patients with drug-induced liver injury by Yue Zhang, Chuan Lu, Jingying Xu, Qiqi Ma, Mei Han, Li Ying

“…We used the area under the receiver operating characteristics curves (AUC) to test the model performances. Backward stepwise regression, best subset and logistic regression models were employed for feature selection and model building. …”
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Non-Contact Oxygen Saturation Estimation Using Deep Learning Ensemble Models and Bayesian Optimization by Andrés Escobedo-Gordillo, Jorge Brieva, Ernesto Moya-Albor

“…We applied the Eulerian Video Magnification technique using the Hermite Transform (EVM-HT) as a feature detector to feed a Three-Dimensional Convolutional Neural Network (3D-CNN). …”
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LFN-YOLO: precision underwater small object detection via a lightweight reparameterized approach by Mingxin Liu, Mingxin Liu, Yujie Wu, Ruixin Li, Cong Lin, Cong Lin

“…This modification effectively enhances the detection performance for small objects. Furthermore, We employed the Generalized Feature Pyramid Network (GFPN) for feature fusion in the network's neck, enhancing the network's adaptability to features of varying scales. …”
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Hyperspectral Imaging for Non-Destructive Moisture Prediction in Oat Seeds by Peng Zhang, Jiangping Liu

“…PCA exhibited superior performance in information compression and modeling stability. …”
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Predictive Analytics in Maternal Health: A Machine Learning Approach for Classification of Preeclampsia by Pakiza Amin, Saima Gulzar Ahmad, Hikmat Ullah Khan, Ehsan Ullah Munir, Naeem Ramzan

“…To improve the classification performance, several models were created, with an emphasis on ensemble learning methods. …”
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Development of the Incident Management Model in an Enterprise Information System Based on a Three-Tier Architecture Using Key (Relevant) Metrics by A. A. Mikryukov, A. V. Kuular

“…A comparative analysis of the existing model of the incidents’ management process and the proposed model is performed. …”
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Sports video temporal action detection technology based on an improved MSST algorithm by Lai Lixin, Fang Yu

“…To optimize sports video data processing and temporal action detection, an improved multi-level spatiotemporal transformer network model is proposed. The model first optimizes the initial feature extraction of videos through an unsupervised video data preprocessing model based on deep residual networks. …”
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