Biomarkers troponin and procalcitonin in addition to CRB-65 enhance risk stratification in patients with community-acquired pneumonia by Imrana Farhat, Maciej Rosolowski, Katharina Ahrens, Jasmin Lienau, Peter Ahnert, Mathias Pletz, Gernot Rohde, Jan Rupp, Markus Scholz, Martin Witzenrath, the CAPNETZ Study Group

“…TnT-hs exhibited the highest predictive performance among individual features (area under the receiver operating characteristic curve, AUC=0.74), followed closely by PCT (AUC=0.73). …”
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Research on Quantitative Analysis Method of Infrared Spectroscopy for Coal Mine Gases by Feng Zhang, Yuchen Zhu, Lin Li, Suping Zhao, Xiaoyan Zhang, Chaobo Chen

“…The selected variables were then used as input features for building a model with a backpropagation (BP) neural network. …”
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An Analysis on Tendency Components on Strategic Approach in the Process of Urban Planning in Iran by Hosseini Mahnaz, Ghadami Mostafa

“…Cycle approach, process and partnership as an appropriate model can replaced centralized approach to comprehensive planning features uncompromising and unrealistic used in developing countries, including our country. 2-Materials and Methods The required data and information were collected in two ways, including measuring and library survey. …”
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Tumor-Infiltrating Immune Cells and PD-L1 as Prognostic Biomarkers in Primary Esophageal Small Cell Carcinoma by Xiao Wu, Xiurong Ke, Yangpeng Ni, Liping Kuang, Fan Zhang, Yusheng Lin, Wan Lin, Xiao Xiong, Haihua Huang, Xianjie Lin, Hao Zhang

“…The Kaplan-–Meier analysis indicated several factors that contribute to poor survival, including negative PD-L1 expression, rich CD4 expression, rich FoxP3 expression, a low CD8/CD4 ratio, and a high FoxP3/CD8 ratio. A nomogram model was constructed and showed good performance for survival prediction. …”
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A multi-module enhanced YOLOv8 framework for accurate AO classification of distal radius fractures: SCFAST-YOLO by Yu Wang, Haifu Sun, Tiankai Jiang, JunFeng Shi, JunFeng Shi, Qin Wang, Qin Wang, Hongwei Yang, Hongwei Yang, Yusen Qiao

“…Secondly, we develop the C2f-Faster-EMA module that preserves fine-grained spatial details through optimized information pathways and statistical feature aggregation. Third, our Feature-Driven Pyramid Network facilitates multi-resolution feature fusion across scales for improved detection. …”
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A pregeneration–recognition method of detecting weak seafloor echoes for full-waveform airborne LiDAR bathymetry by Yadong Guo, Wenxue Xu, Yanxiong Liu, Fanlin Yang, Xue Ji, Yikai Feng, Qiuhua Tang

“…Then, an adaptive ellipsoidal neighborhood related to the point density is used to select neighborhood points, and eigenvalue-based spatial features are calculated. Finally, a back propagation neural network (BPNN) model is constructed using the points generated from surface–seafloor shots, and the seafloor points in seafloor-undefined shots are obtained by optimizing the BPNN results. …”
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RF-PSignal: The Smart Home Gesture Recognition System Based on Channel-Wise Topology and Self-Adaptive Attention by Xiaohang Zhang, Chunhong Yue, Yajun Zhang, Kun Liang, Yanxiang Li

“…Unlike most existing studies that rely on time-series signals for feature extraction and pattern recognition, the system achieves outstanding performance and computational efficiency through a time-series-to-image transformation algorithm and lightweight model design. …”
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Solar Energy Forecasting Using Machine Learning Techniques for Enhanced Grid Stability by Attuluri R. Vijay Babu, N. Bharath Kumar, Rajanand Patnaik Narasipuram, Soundhar Periyannan, Alireza Hosseinpour, Aymen Flah

“…Historical solar power and weather datasets were used to train and evaluate the models across multiple performance metrics. Among the models, the Gradient Boosting Regressor demonstrated the best performance, achieving an <inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> of 0.827, RMSE of 399.44, and MAE of 253.62, marking a significant improvement over baseline models. …”
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Classifying social position with social media behavioral data by Júlia Koltai, Zsófia Rakovics, Zoltán Kmetty, Kata Számel, Borbála Ungvári, Bendegúz Váradi, Ákos Huszár

“…The models based on purely observed digital behavior could identify those in the lowest social position with the highest performance. …”
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Substituted 1,4-naphthoquinones for potential anticancer therapeutics: In vitro cytotoxic effects and QSAR-guided design of new analogs by Veda Prachayasittikul, Prasit Mandi, Ratchanok Pingaew, Supaluk Prachayasittikul, Somsak Ruchirawat, Virapong Prachayasittikul

“…Compound 11 was found to be the most potent and selective anticancer agent against all tested cell lines (IC50 = 0.15 – 1.55 μM, selectivity index = 4.14 – 43.57). QSAR modelling was performed to elucidate key structural features influencing activities against four cancer cell lines. …”
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ColoViT: a synergistic integration of EfficientNet and vision transformers for advanced colon cancer detection by Bukka Sathyanarayana, Sreedevi Alampally, Ramakrishna Akella, Veera Venkata Raghunath Indugu

“…EfficientNet contributes scalability and high performance in feature extraction, while Vision Transformers effectively capture the global contextual information within colonoscopic images. …”
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Plant leaf disease detection using vision transformers for precision agriculture by Murugavalli S, Gopi R

“…Transfer learning using pre-trained ViTs reduces computing load and improves feature extraction. The model may be adjusted by hyperparameter tuning and adaptive learning rate scheduling for robust performance with minimal overfitting. …”
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Classification of offshore wind grid-connected power quality disturbances based on fast S-transform and CPO-optimized convolutional neural network. by Minan Tang, Hongjie Wang, Jiandong Qiu, Zhanglong Tao, Tong Yang

“…Secondly, the CPO algorithm is used to optimize the convolutional neural network and determine the best hyperparameters so that the classifier achieves the optimal classification performance. Then, the CPO-CNN classification model is used for feature extraction and feature selection of the time-frequency diagrams and classification of multiple power quality disturbances. …”
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Who benefits from adjuvant chemotherapy? Identification of early recurrence in intrahepatic cholangiocarcinoma patients after curative-intent resection using machine learning algor... by Qi Li, Hengchao Liu, Yubo Ma, Zhenqi Tang, Chen Chen, Dong Zhang, Zhimin Geng

“…Among the various prediction models, LightGBM demonstrated superior performance compared to other models in the testing set, exhibiting higher sensitivity, specificity, and accuracy. …”
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AI-Driven Prediction of Symptom Trajectories in Cancer Care: A Deep Learning Approach for Chemotherapy Management by Joseph Finkelstein, Aref Smiley, Christina Echeverria, Kathi Mooney

“…The findings demonstrate that both CNN’s temporospatial feature extraction and LSTM’s temporal modeling effectively capture escalation patterns in symptom progression. …”
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Binarized Neural Networks for Resource-Efficient Spike Sorting by Luca M. Meyer, Majid Zamani, Andreas Demosthenous

“…This work presents a binarized neural network for spike sorting that narrows the performance gap between recently developed binarized models and more accurate full-precision models. …”
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YOLO-RDM: Innovative Detection Methods for Eggplants and Stems in Complex Natural Environment by Qin Liu, Zhibin Zhou, Lu Xiong, Meilian Lu, Jingwen Ouyang

“…Additionally, the F1 score improved by 4.96%, reaching 89.09%. This model demonstrates superior detection performance and robustness for both eggplants and their stems, providing valuable technical support for the automation of eggplant harvesting.…”
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A Parameter-Optimized DBN Using GOA and Its Application in Fault Diagnosis of Gearbox by Jingbo Gai, Junxian Shen, He Wang, Yifan Hu

“…The experimental results show that this method could effectively improve the self-adaptive feature extraction ability of the model as well as its accuracy of fault diagnosis, which has better generalization performance.…”
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A fast identification method for multi-joint robot load based on improved Fourier neural network by Xia Yue, Jionghao Mo, Zhibin Li, Haiteng Li, Chunliang Zhang, Shangbin Long

“…In this method, two neural network models are combined to effectively identify different feature sets in high-dimensional data, so as to realize efficient load parameter identification and provide reference for parameter identification of complex nonlinear systems.…”
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Uncertainty quantification for overshoots of tipping thresholds by K. Lux-Gottschalk, P. D. L. Ritchie, P. D. L. Ritchie

“…However, in the real world or in complex models, critical thresholds and other system features, such as inherent timescales and the system's linear restoring force after perturbations, are highly uncertain. …”
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