Machine learning model for prediction of palliative care phases in patients with advanced cancer: a retrospective study by Junchen Guo, Yunyun Dai, Sishan Jiang, Junqingzhao Liu, Xianghua Xu, Yongyi Chen

“…The Gradient Boosting Decision Tree in the machine learning algorithm to establish a palliative care phase prediction model and evaluated the prediction performance of this model. …”
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Addressing Spatial Variability in Estimating Cover Management Factor of Soil Erosion Models using Geoinformatics: A Case Study of Netravati Catchment, Karnataka, India by Waleed Makhdumi, Shwetha H. R., G. S. Dwarakish, Jagadeesha B. Pai

“…This study aims to improve the accuracy of C factor estimates for the Netravati catchment present in the Western Ghats and Coastal Plains of India by using the Random Forest Algorithm and Sentinel 2 satellite data. The research examined five commonly used Normalized Difference Vegetation Index (NDVI) based C factor estimating equations and found that they inadequately represented local vegetation dynamics in the study area. …”
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A Shared Control Method of Multiobjective Motion Fusion for Surgical Robot by Xilin Xiao, Xiaojian Li, Hangjie Mo, Yudong Shi, Jing Fang, Ling Li, Bo Ouyang, Shanlin Yang

“…In addition, a state feedback mechanism with prediction and evaluation model is developed to balance the control inputs of different control objectives. …”
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Is human-like decision making explainable? Towards an explainable artificial intelligence for autonomous vehicles by Jiming Xie, Yan Zhang, Yaqin Qin, Bijun Wang, Shuai Dong, Ke Li, Yulan Xia

“…These findings have the potential to inform ongoing research on brain-like neural learning and could function as a catalyst for developing swifter and more potent algorithmic solutions in the realm of intelligent transportation.…”
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Machine Learning-Based VO₂ Estimation Using a Wearable Multiwavelength Photoplethysmography Device by Chin-To Hsiao, Carl Tong, Gerard L. Coté

“…Unlike conventional wearables that rely on static formulas for VO₂ max estimation, our algorithm leverages the data from the PPG wearable and uses the Beer–Lambert Law with inputs from five wavelengths (670 nm, 770 nm, 810 nm, 850 nm, and 950 nm), incorporating the isosbestic point at 810 nm to differentiate oxy- and deoxy-hemoglobin. …”
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INTERGENIC INTERACTIONS OF TUMOR NECROSIS FACTOR ALPHA, INTERLEUKIN 17, AND OSTEOPROTEGERIN IN THE IMMUNOPATHOGENESIS OF RHEUMATOID ARTHRITIS IN THE RUSSIAN POPULATION OF THE CHELY... by Yulia Chumacheva, Daria Stashkevich, Tatiana Suslova, Daria Shmelkova, Aleksandra Burmistrova

“…To analyse the data we applied the multifactor dimensionality reduction (MDR) algorithm, which constructs predictive case–control models and evaluates their robustness through ten-fold cross-validation and permutation testing.The algorithm identified three most informative combinations comprising four to six SNPs each; every combination showed statistical significance and high predictive accuracy. …”
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From genes to therapy: a lipid Metabolism-Related genetic risk model predicts HCC outcomes and enhances immunotherapy by Lei Xu, Ting Xiao, Tengfei Chao, Huihua Xiong, Wei Yao

“…The immune signature associated with the risk model was also evaluated by the CIBERSORT algorithm, tumor immune dysfunction and exclusion algorithm, and single sample gene set enrichment analysis. …”
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Digital and online symptom checkers and health assessment/triage services for urgent health problems: systematic review by Andrew Booth, Duncan Chambers, Anna J Cantrell, Maxine Johnson, Louise Preston, Susan K Baxter, Janette Turner

“…Diagnostic accuracy varied between different systems but was generally low. Algorithm-based triage tended to be more risk averse than that of health professionals. …”
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Data-driven cluster analysis on the association of aging, obesity and insulin resistance with new-onset diabetes in Chinese adults: a multicenter retrospective cohort study by Yazhi Wang, Mingkang Zhang, Peng Wang

“…After clustering, multivariate Cox proportional hazards regression analysis was used to evaluate and compare the risk of diabetes incidence among different clusters.ResultsThe study population comprising 12,607 subjects was clustered into four distinct groups: Cluster 1 (metabolic health cluster), Cluster 2 (low HDL-C cluster), Cluster 3 (old age and mild metabolic disorder cluster), and Cluster 4 (severe obesity and insulin resistance cluster). …”
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Modeling Worldwide Tree Biodiversity Using Canopy Structure Metrics from Global Ecosystem Dynamics Investigation Data by Jin Xu, Kjirsten Coleman, Volker C. Radeloff, Melissa Songer, Qiongyu Huang

“…Using Forest Global Earth Observatory (ForestGEO) data, we developed three models using the random forest algorithm to predict global tree species richness across climate zones, including a dynamic habitat index (DHI)-only model, a GEDI-only model, and a combined GEDI-DHI model. …”
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A model of indoor thermal condition based on traditional acehnese houses using artificial neural network by Muslimsyah, Abdul Munir, Yuwaldi Away, Abdullah, Teuku Yuliar Arif, Andri Novandri

“…The study employs an ANN (Artificial Neural Network) algorithm to predict thermal condition parameters including indoor: temperature, humidity, and wind speed. …”
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Profile of the HIV epidemic in Cape Verde: molecular epidemiology and drug resistance mutations among HIV-1 and HIV-2 infected patients from distinct islands of the archipelago. by Isabel Inês M de Pina-Araujo, Monick L Guimarães, Gonzalo Bello, Ana Carolina P Vicente, Mariza G Morgado

“…Algorithm Homepage, respectively. Among the 221 patients (169 [76.5%] HIV-1, 43 [19.5%] HIV-2 and 9 [4.1%] HIV-1/HIV-2 co-infections), 67% were female. …”
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Enhancing Drought Forecast Accuracy Through Informer Model Optimization by Jieru Wei, Wensheng Tang, Pakorn Ditthakit, Jiandong Shang, Hengliang Guo, Bei Zhao, Gang Wu, Yang Guo

“…The performance of these models was evaluated using the root mean square error (RMSE), Nash–Sutcliffe efficiency coefficient (NSE), and Mean Absolute Error (MAE). …”
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Predicting breeding values in Murrah buffaloes using random regression models by ANAND JAIN, ASHISH RANJAN, I D GUPTA, H K SINGH

“…Various random regression models with different order of Legendre polynomials for permanent environmental and genetic effects were constructed to evaluate Murrah buffaloes under field condition. …”
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Enhancing weld quality of novel robotic-arm arc welding: Vision-based monitoring, real-time control seam tracking by Aman Sharma, Rishabh Chaturvedi, Kamal Sharma, Saad Abrahim Binhowimal, Jayant Giri, T. Sathish

“…New software is used for welding seam monitoring to examine different features of robotic arm arc welding. The software system comprises several components: welding voltage regulation, analytical parameters, image capture or analysis using enhanced algorithms, weld experts’ database, robot coordination, and trajectory operations management. …”
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Unraveling the structural and functional consequences of non-synonymous single-nucleotide polymorphisms (nsSNPs) in human SOCS2: an in silico approach by Tanvir Hossain, Md. Nur Islam, Md. Anwar Hossain, Md. Mofizur Rahman, Mohammed Mafizul Islam, Shipan Das Gupta

“…Results In this study, we examined nsSNPs in the human SOCS2 gene to evaluate their effects on protein stability, structure, and function through in silico approaches. …”
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A Privacy-Preserving Polymorphic Heterogeneous Security Architecture for Cloud–Edge Collaboration Industrial Control Systems by Yukun Niu, Xiaopeng Han, Chuan He, Yunfan Wang, Zhigang Cao, Ding Zhou

“…Comprehensive evaluations using natural gas pipeline pressure control and smart grid voltage control systems demonstrate superior performance: the proposed method achieves 100% system availability compared to 62.57% for static redundancy and 86.53% for moving target defense, maintains 99.98% availability even under common-mode attacks (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mn>10</mn><mrow><mo>−</mo><mn>2</mn></mrow></msup></semantics></math></inline-formula> probability), and consistently outperforms moving target defense methods integrated with state-of-the-art detection mechanisms (99.7790% and 99.6735% average availability when false data deviations from true values are 5% and 3%, respectively) across different attack detection scenarios, validating its effectiveness in defending against availability attacks and privacy leakage threats in cloud–edge collaboration environments.…”
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Identification and validation of hub genes associated with biotic and abiotic stresses by modular gene co-expression analysis in Oryza sativa L. by Izreen Izzati Razalli, Muhammad-Redha Abdullah-Zawawi, Rabiatul Adawiah Zainal Abidin, Sarahani Harun, Muhamad Hafiz Che Othman, Ismanizan Ismail, Zamri Zainal

“…A modular gene co-expression (mGCE) analysis was conducted, followed by gene set enrichment analysis to evaluate the upregulation of module activity across different stress conditions. …”
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MRI-based machine learning radiomics for prediction of HER2 expression status in breast invasive ductal carcinoma by Hong-Jian Luo, Jia-Liang Ren, Li mei Guo, Jin liang Niu, Xiao-Li Song

“…A simulated annealing algorithm was used for key feature selection. Two classification tasks were performed: task 1, the classification of HER2-positive vs. …”
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Rotor Location During Atrial Fibrillation: A Framework Based on Data Fusion and Information Quality by Miguel A. Becerra, Diego H. Peluffo-Ordoñez, Johana Vela, Cristian Mejía, Juan P. Ugarte, Catalina Tobón

“…First, EGMs were contaminated with different types of noise and artifacts (power-line interference, spikes, loss of samples, and loss of resolution) to assess tolerance. …”
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