Efficacy and safety of ruxolitinib combined with steroids for first-line treatment of acute graft-versus-host disease after hematopoietic stem cell transplantation: a single-center... by Yan Yang, Yuan Huo, Dong Zhou, Zhijie Kang, Yanan Huang, Ying Wang, Guangjun Fan, Liyuan Ma, Jinsong Yan, Jinsong Yan, Jinsong Yan

“…Steroids are the standard first-line treatment for acute GVHD (aGVHD); however, standardized treatment algorithms for patients who do not respond to steroid therapy are lacking. …”
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Construction of a risk prediction model for occupational noise-induced hearing loss using routine blood and biochemical indicators in Shenzhen, China: a predictive modelling study by Wenting Feng, Wen Zhang, Yan Guo, Naixing Zhang, Liang Zhou, Dafeng Lin, Linlin Chen, Caiping Li, Liuwei Shi, Xiangli Yang, Peimao Li, Dianpeng Wang

“…Routine blood and biochemical indicators were extracted from the case data, and a range of machine learning algorithms including extreme gradient boosting (XGBoost) were employed to construct predictive models. …”
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Design and Implementation of a Deep Learning-Based Hand Gesture Recognition System for Rehabilitation Internet-of-Things (RIoT) Environments Using MediaPipe by Nurul Hanis Mohd Dhuzuki, Ahmad Anwar Zainuddin, Nur Anis Sofea Kamarul Zaman, Alin Nur Maisarah Ahmad Razmi, Wonderful Shammah Kaitane, Asmarani Ahmad Puzi, Mohd Naqiuddin Johar, Maslina Yazid, Nor Azlin Mohd Nordin, Shahrul Naim Sidek, Hasan Firdaus Mohd Zaki

“…The methodology involves the integration of MediaPipe for detecting hand landmarks and adaptive sensitivity algorithms to ensure reliable recognition across different environments, such as varying lighting and hand positions. …”
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Development and validation of a machine learning-based risk prediction model for stroke-associated pneumonia in older adult hemorrhagic stroke by Yi Cao, Yi Cao, Haipeng Deng, Shaoyun Liu, Xi Zeng, Yangyang Gou, Weiting Zhang, Yixinyuan Li, Hua Yang, Min Peng

“…Model performance was compared using Delong's test or Bootstrap test, while sensitivity, specificity, accuracy, precision, recall, and F1-score evaluated predictive efficacy. …”
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Three-Year On-Orbit Radiometric Performance of the SDGSAT-1 Multispectral Imager (MSI) by Lin Yan, Enchuan Qiao, Changyong Dou, Hao Zhang, Zhenzhen Cui, Yonghong Hu, Xiao-Ming Li, Jinlong Ai

“…Further efforts including enhanced calibration algorithms developing, cross radiometric calibration with payloads have good radiometric performance will be conducted. …”
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An IoT-enabled AI system for real-time crop prediction using soil and weather data in precision agriculture by MD Shaifullah Sharafat, Nilavro Das Kabya, Rahimul Islam Emu, Mehrab Uddin Ahmed, Jakaria Chowdhury Onik, Mohammad Aminul Islam, Riasat Khan

“…Several machine learning algorithms, including Random Forest, Gradient Boosting, and Stacking ensembles, as well as deep learning models such as TabNet, were evaluated for crop prediction. …”
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Knowledge Distillation in Object Detection for Resource-Constrained Edge Computing by Arief Setyanto, Theopilus Bayu Sasongko, Muhammad Ainul Fikri, Dhani Ariatmanto, I. Made Artha Agastya, Rakandhiya Daanii Rachmanto, Affan Ardana, In Kee Kim

“…We compare various KD algorithms to identify the technique that produces a smaller model with the modest accuracy drop. …”
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A systematic comparison of short-term and long-term mortality prediction in acute myocardial infarction using machine learning models by Yawei Yang, Junjie Tang, Liping Ma, Feng Wu, Xiaoqing Guan

“…CBC parameters and renal biomarkers were pivotal in short-term models, while therapeutic interventions gained prominence over time. …”
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Improved estimation of two-phase capillary pressure with nuclear magnetic resonance measurements via machine learning by Oriyomi Raheem, Misael M. Morales, Wen Pan, Carlos Torres-Verdín

“…One of the main challenges in characterizing pore structure is how to use data from core plugs to establish a relationship with microscopic pore and throat properties, enabling more accurate predictions of capillary pressure. While special core analysis laboratory experiments are effective, they are time-consuming and expensive. …”
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Construction and analysis of a prognostic risk scoring model for gastric cancer anoikis-related genes based on LASSO regression by Ai CHEN, Xiaowei CHEN, Yanan WANG, Xiaobing SHEN

“…Gene expression levels in gastric cancer clinical samples and cells were detected by real-time quantitative PCR (RT-qPCR); Kaplan-Meier (KM) survival curves, univariate and multivariate Cox regression analyses were used to verify the predictive efficiency of the prognostic risk scoring model for the prognosis of gastric cancer patients; CIBERSORT and ESTIMATE algorithms were used to analyze the immune cell infiltration levels in patients with different risk groups; the correlation between risk scores and immune checkpoint expression levels in gastric cancer patients was analyzed using the R package "ggplot2" and "ggExtra", and the correlation between tumor mutation burden (TMB) and risk scores was assessed; chemotherapy drug sensitivity analysis was used to evaluate the value of the constructed prognostic risk scoring model in gastric cancer chemotherapy. …”
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Molecular subtype of recurrent implantation failure reveals distinct endometrial etiology of female infertility by Jing Yang, Lingtao Yang, Ying Zhou, Fengyang Cao, Hongkun Fang, Huan Ma, Jun Ren, Chunyu Huang, Lianghui Diao, Qiyuan Li, Qionghua Chen

“…Abstract Background Recurrent implantation failure (RIF) remains a significant barrier in assisted reproductive technology (ART), where multiple transfers of high-quality embryos fail to achieve pregnancy. While embryo-related factors have been extensively investigated, the contribution of endometrial dysfunction to RIF remains poorly characterized. …”
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Efficiency and safety of the Russian-made KERATOLINK device used to treat patients with stage I–II keratoconus and pellucid marginal corneal degeneration by A. T. Khandzhyan, E. N. Iomdina, A. V. Ivanova, A. S. Sklyarova, N. V. Khodzhabekyan, I. V. Manukyan

“…The use of local UVCL and accelerated algorithms with a significant reduced exposure time improves the comfort and tolerability of the procedure, and also reduces the risk of complications. …”
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Research on Hybrid Architecture Neural Networks for Time Series Prediction by Fujin Zhuang, Xiao Chen, Punyaphol Horata, Khamron Sunat

“…This multi-module collaborative architecture effectively processes multi-scale features of time series data while providing model interpretability. Through comparative analysis of various optimization algorithms’ convergence performance and prediction accuracy, this study found that the AdamW optimizer, with its effective weight decay mechanism and adaptive learning rate, demonstrated superior performance in training stability and generalization capability, with MSE and R2 metrics outperforming traditional optimizers. …”
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Predicting CO₂ and H₂ Solubility in Pure Water and Various Aqueous Systems: Implication for CO₂–EOR, Carbon Capture and Sequestration, Natural Hydr... by Promise O. Longe, David Kwaku Danso, Gideon Gyamfi, Jyun Syung Tsau, Mubarak M. Alhajeri, Mojdeh Rasoulzadeh, Xiaoli Li, Reza Ghahfarokhi Barati

“…These results demonstrate that the models can accurately predict solubility over a wide range of conditions while remaining computationally efficient compared to traditional models. …”
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Biological and prognostic insights into the prostaglandin D2 signaling axis in lung adenocarcinoma by Qiang Liu, Huiguo Chen, Dongfang Tang, Huibiao Zhang, Shaogeng Chen, Yiran Meng, Boying Zheng, Fei Liu, Jing Zhou, Wen Zhang

“…The TCGA‐LUAD datasets was used to estimate and analyze immune cell infiltration levels and tumor hot score using the ESTIMATE and ssGSEA algorithms. Additionally, survival analysis was conducted on genes within relative signaling axis. …”
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Emisión Acústica y Redes Neuronales para Modelado y Caracterización del Proceso de Soldadura por Fricción Agitación by Emilio Jiménez Macías, Angel Sánchez Roca, Hipólito Carvajal Fals, Julio Blanco Fernández, Juan C. Sáenz-Diez Muro

“…Statistical and temporal parameters of discomposed EA signals using Wavelet Transform (WT) have been used as input of the ANN, while the outputs of model include the welding parameters: tool rotation speed and travel speed, as well as the tool profile. …”
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Machine learning applications in forecasting patient satisfaction and clinical outcomes after carpal tunnel release: a retrospective study by Zohreh Manoochehri, Sara Manoochehri, Seyed Reza Bagheri, Alireza Abdi, Ehsan Alimohammadi

“…Four machine learning algorithms—random forest (RF), gradient boosting machine (GBM), support vector machine (SVM), and k-nearest neighbors (k-NN)—were used to predict these outcomes. …”
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MMAgentRec, a personalized multi-modal recommendation agent with large language model by Xiaochen Xiao

“…Specifically, LightGCN achieves an accuracy of 0.9210, while DualGNN reaches 0.9285, both falling short of the proposed model’s performance. …”
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Role of ARRB1 in prognosis and immunotherapy: A Pan-Cancer analysis by Yingquan Ye, Yingquan Ye, Haili Jiang, Haili Jiang, Yue Wu, Yue Wu, Gaoxiang Wang, Gaoxiang Wang, Yi Huang, Yi Huang, Weijie Sun, Mei Zhang, Mei Zhang

“…ESTIMATE and CIBERSORT algorithms were performed to assess immune infiltration. …”
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Artificial intelligence in hospital infection prevention: an integrative review by Rabie Adel El Arab, Zainab Almoosa, May Alkhunaizi, May Alkhunaizi, Fuad H. Abuadas, Joel Somerville, Joel Somerville

“…Comparative data suggest that while both machine learning and deep learning approaches perform well, some deep learning models may offer slight advantages in complex data environments. …”
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