Burden of chronic spontaneous urticaria in Italy through healthcare resource utilization and direct costs: a retrospective analysis of real-world using administrative healthcare da... by Giulia Ronconi, Letizia Dondi, Silvia Calabria, Leonardo Dondi, Irene Dell’Anno, Lucia Casoli, Diletta Valsecchi, Ornella Bonavita, Eustachio Nettis, Nello Martini, Carlo Piccinni

“…Conclusions During the first year following the new CSU diagnosis, a lower than recommended antihistamines dispensation while an elevated use of OCS and a low and delayed omalizumab initiation after CSU exacerbation were observed, suggesting the urgent need to optimize treatment management to limit the burden on patients and healthcare systems.…”
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Design and simulation of a 5 KW solar-powered hybrid electric vehicle charging station with a ANN–Kalman filter MPPT and MPC-based inverter control for reduced THD by Youness Hakam, Hajar Ahessab, Ahmed Gaga, Mohamed Tabaa, Benachir El Hadadi

“…By integrating a Kalman filter with Artificial Neural Networks (ANN) for Maximum Power Point Tracking (MPPT), the system optimizes energy capture from photovoltaic (PV) panels, even in severe weather conditions and partial shading. …”
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Identifying low-risk breast cancer patients for axillary biopsy exemption: a multimodal preoperative predictive model by Jiaqi Zhang, Jianing Zhang, Zhihao Liu, Yudong Zhou, Xiaoni Zhao, Yalong Wang, Danni Li, Jinsui Du, Chenglong Duan, Yi Pan, Qi Tian, Feiqian Wang, Ke Wang, Lizhe Zhu, Bin Wang

“…To optimize the utilization of biopsy, this study established a multimodal predictive framework that preoperatively assesses axillary lymph node (ALN) status, thereby triaging candidates for ultrasound-guided axillary biopsy. …”
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Building a composition-microstructure-performance model for C–V–Cr–Mo wear-resistant steel via the thermodynamic calculations and machine learning synergy by Shuaiwu Tong, Shuaijun Zhang, Chong Chen, Tao Jiang, Peng Li, Shizhong Wei

“…Furthermore, feature importance analysis, conducted using the Random Forest algorithm, revealed significant differences in the factors affecting sliding friction and abrasive wear. …”
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Hydropower system in the Yarlung-Tsangpo Grand Canyon can mitigate flood disasters caused by climate change by Fengbo Zhang, Qin Yang, Jianhua Wang, Huan Liu, Qinghui Zeng, Long Yan, Baolong Zhao, Jiaxuan Tang, Kang Zhao, Yining Zang, Wei Liu, Peng Hu

“…Here we evaluate the water-energy-ecosystem nexus in this hydropower system using the Water and Energy Transfer Processes in Large River Basins model and the Non-Dominated Sorting Genetic Algorithm III model. Key findings reveal that reservoir operations with medium replenishment flow (1000 m³ s−1) during dry periods achieve an optimal balance among hydropower generation annually (2231 × 108 kWh), flood mitigation (peak clipping rate 22.8%), and minimal ecosystem impact (eco-index 0.45). …”
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The Role of Immunohistochemistry as a Surrogate Marker in Molecular Subtyping and Classification of Bladder Cancer by Tatiana Cano Barbadilla, Martina Álvarez Pérez, Juan Daniel Prieto Cuadra, Mª Teresa Dawid de Vera, Fernando Alberca-del Arco, Isabel García Muñoz, Rocío Santos-Pérez de la Blanca, Bernardo Herrera-Imbroda, Elisa Matas-Rico, Mª Isabel Hierro Martín

“…Further research is required to determine the optimal combination of markers, establish a consensus diagnostic algorithm, and validate IHC through large-scale trials. …”
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Comparative performance evaluation of quartz and snail shell powders modified concrete: Mechanical, machine learning, and microstructural assessments by Md. Habibur Rahman Sobuz, Md. Kanan Chowdhury Tilak, SM Arifur Rahman, Fahim Shahriyar Aditto, Faiz Uddin Ahmed Shaikh, Md. Kawsarul Islam Kabbo, M Jameel, Md. Munir Hayet Khan

“…As seen by adding the optimal SSP replacements of eco-friendly concrete mixtures, it boosted mechanical strength while lowering carbon footprint, making it a sustainable building concrete construction.…”
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Computer-Aided Diagnosis and Staging of Pancreatic Cancer Based on CT Images by Min Li, Xiaohan Nie, Yilidan Reheman, Pan Huang, Shuailei Zhang, Yushuai Yuan, Chen Chen, Ziwei Yan, Cheng Chen, Xiaoyi Lv, Wei Han

“…The least absolute shrinkage and selection operator (LASSO) algorithm was chosen for feature selection. In contrast to no feature selection, the model optimization time decreased by 19.94 seconds while maintaining precision. …”
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Using proximal sensor data for soil salinity management and mapping by Yan GUO, Yin ZHOU, Lian-qing ZHOU, Ting LIU, Lai-gang WANG, Yong-zheng CHENG, Jia HE, Guo-qing ZHENG

“…We concluded that two management zones are optimal to guide precision management. Zone A had an average salinity level of about 165 mS m−1, in which salt-tolerant crops, such as cotton and barley can grow normally, while crops such as soybean and cowpeas may be planted using leaching and increasing the mulching film methods to reduce the accumulation of salt in surface soil. …”
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Understanding the flowering process of litchi through machine learning predictive models by SU Zuanxian, NING Zhenchen, WANG Qing, CHEN Houbin

“…The algorithms (RF and STR) with the smallest Mean Absolute Error (MAE) and the highest residual error (RMSE) and the highest correlation coefficient (RP2) were selected for further parameter optimization and evaluation. …”
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Transcriptional fingerprinting of regulatory T cells: ensuring quality in cell therapy applications by Zhang Cheng, Li-Jie Wang, Yuchi Honaker, Steven A. Cincotta, Claire E. Page, Sydney Vollhardt, Victor Yuan, S. Alice Long, Yuanyuan Xiao, Joshua N. Beilke, Joseph R. Arron, Jeffrey A. Bluestone

“…We employed a non-parametric algorithm to score Treg manufacturing products for their cell identity and expansion fingerprints.ResultsThe identity fingerprint reflects Treg cell identity by effectively distinguishing Treg from Teff cells irrespective of their activation status, with 100% sensitivity and specificity, while the expansion fingerprint discriminates expanded versus endogenous Treg or Teff cells. …”
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Acute kidney disease in hospitalized pediatric patients: risk prediction based on an artificial intelligence approach by Lingyu Xu, Siqi Jiang, Chenyu Li, Xue Gao, Chen Guan, Tianyang Li, Ningxin Zhang, Shuang Gao, Xinyuan Wang, Yanfei Wang, Lin Che, Yan Xu

“…Predictive models were constructed using eight machine learning algorithms and two ensemble algorithms, with the optimal model identified through AUROC. …”
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Machine learning-based integration develops relapse related signature for predicting prognosis and indicating immune microenvironment infiltration in breast cancer by Junyi Li, Shixin Li, Dongpo Zhang, Yibing Zhu, Yue Wang, Xiaoxiao Xing, Juefei Mo, Yong Zhang, Daixiang Liao, Jun Li

“…To address these limitations, this study systematically analyzed RNA-seq high-throughput data and combined 10 machine learning algorithms to construct 117 models. The optimal algorithm combination, StepCox[both] and ridge regression, was identified, and an immune-related gene signature (IRGS) composed of 12 genes was developed. …”
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Frailty in older adults patients: a prospective observational cohort study on subtype identification by Zhikai Yang, Chen Ji, Ting Wang, Wei He, Yuhao Wan, Min Zeng, Di Guo, Lingling Cui, Hua Wang

“…This study applied the K-means clustering algorithm to analyze 27 variables, determining the optimal cluster number using the Elbow method and Silhouette coefficient. …”
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Developing a Machine Learning Model for Predicting 30-Day Major Adverse Cardiac and Cerebrovascular Events in Patients Undergoing Noncardiac Surgery: Retrospective Study by Ju-Seung Kwun, Houng-Beom Ahn, Si-Hyuck Kang, Sooyoung Yoo, Seok Kim, Wongeun Song, Junho Hyun, Ji Seon Oh, Gakyoung Baek, Jung-Won Suh

“…Among 46,225 patients of the Seoul National University Bundang Hospital, MACCE occurred in 4.9% (2256/46,225), including myocardial infarction (907/46,225, 2%) and stroke (799/46,225, 1.7%), while in-hospital mortality was 0.9% (419/46,225). …”
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A Fusion XGBoost Approach for Large-Scale Monitoring of Soil Heavy Metal in Farmland Using Hyperspectral Imagery by Xuqing Li, Huitao Gu, Ruiyin Tang, Bin Zou, Xiangnan Liu, Huiping Ou, Xuying Chen, Yubin Song, Wei Luo, Bin Wen

“…The optimal model was extended to the entire region for drawing the spatial distribution map of soil heavy metal content. …”
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Magnetic Resonance Imaging Texture Analysis Based on Intraosseous and Extraosseous Lesions to Predict Prognosis in Patients with Osteosarcoma by Yu Mori, Hainan Ren, Naoko Mori, Munenori Watanuki, Shin Hitachi, Mika Watanabe, Shunji Mugikura, Kei Takase

“…<b>Objectives:</b> To construct an optimal magnetic resonance imaging (MRI) texture model to evaluate histological patterns and predict prognosis in patients with osteosarcoma (OS). …”
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Stochastic <i>H</i>_∞ Filtering of the Attitude Quaternion by Daniel Choukroun, Lotan Cooper, Nadav Berman

“…Thanks to the bilinear structure of the quaternion state-space model, the algorithm parameters are independent of the state. …”
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CSEPC: a deep learning framework for classifying small-sample multimodal medical image data in Alzheimer’s disease by Jingyuan Liu, Xiaojie Yu, Hidenao Fukuyama, Toshiya Murai, Jinglong Wu, Qi Li, Zhilin Zhang

“…Addressing this obstacle is crucial for improving diagnostic accuracy and optimizing treatment strategies for those affected by AD. …”
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A Deep Learning Method for Photovoltaic Power Generation Forecasting Based on a Time-Series Dense Encoder by Xingfa Zi, Feiyi Liu, Mingyang Liu, Yang Wang

“…Deep learning has become a widely used approach in photovoltaic (PV) power generation forecasting due to its strong self-learning and parameter optimization capabilities. In this study, we apply a deep learning algorithm, known as the time-series dense encoder (TiDE), which is an MLP-based encoder–decoder model, to forecast PV power generation. …”
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