Investigation of the kinematics of mechatronic device drive based on a spatial mechanism by F. F. Khabibullin, R. T. Islamov, T. A. Mustafaev, V. N. Krymova

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Using XBGoost, an interpretable machine learning model, for diagnosing prostate cancer in patients with PSA < 20 ng/ml based on the PSAMR indicator by Dengke Li, Baoyuan Chang, Qunlian Huang

“…After applying the Synthetic Minority Over-sampling TEchnique class balancing on the training set, multiple machine learning models were constructed by using the Least Absolute Shrinkage and Selection Operator (LASSO) feature selection to identify the significant variables. …”
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Research on the Simulation Model of Dynamic Shape for Forest Fire Burned Area Based on Grid Paths from Satellite Remote Sensing Images by Xintao Ling, Gui Zhang, Ying Zheng, Huashun Xiao, Yongke Yang, Fang Zhou, Xin Wu

“…Four machine learning models, such as Random Forest (RF), Gradient Boosting Decision Trees (GBDT), Support Vector Machine (SVM), and Multilayer Perceptron (MLP), were trained using 80% effective samples from four forest fires, and 20% used to verify the above models. …”
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Application of Dynamic 18F-FDG PET/CT for Distinguishing Intrapulmonary Metastases from Synchronous Multiple Primary Lung Cancer by Weize Lv, Min Yang, Hongcheng Zhong, Xiaojin Wang, Shuai Yang, Lei Bi, Jianzhong Xian, Xiaofeng Pei, Xinghua He, Ying Wang, Zhong Lin, Qingdong Cao, Hongjun Jin, Hong Shan

“…The AUC of ΔKi/Dmax for differentiating sMPLC from IPM was 0.80 (cut-off value of Ki=0.0059, sensitivity 79%, specificity 75%, p<0.001). …”
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Experimental studies of dual electric induction spherical electric field intensity sensor in inhomogeneous field of point source by S. V. Biryukov, L. V. Tyukina, A. V. Tyukin

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Fibrinogen-to-Albumin Ratio Predicts Contrast-Induced Nephropathy in Patients after Emergency Percutaneous Coronary Intervention by Zhebin You, Tailin Guo, Fan Lin, Chunjin Lin, Jiankang Chen, Xiaoming Li, Yan Chen, Kaiyang Lin

“…In the multivariate logistic analysis, FAR was an independent predictor of CIN (OR = 3.97; 95% CI, 1.61–9.80; P=0.003) along with perihypotension, age >75 years, and LVEF <45%, and 0.106 was the optimal cutoff value of preprocedural FAR to predict CIN. …”
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HPLC-MS/MS-Mediated Analysis of the Pharmacokinetics, Bioavailability, and Tissue Distribution of Schisandrol B in Rats by Dahu Liang, Zijing Wu, Yanhao Liu, Chao Li, Xianghong Li, Bin Yang, Haitang Xie, Hua Sun

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Screening for monoclonal B-lymphocyte expansion in a hospital-based Chinese population with lymphocytosis: an observational cohort study by Yue Wang, Jing Li, Peng Liu, Jiadai Xu, Zheng Wei

“…CD5 (−) non-CLL-like MBL was observed to be the most common subtype (8, 80%), followed by CLL-like phenotype (1, 10.0%) and atypical CLL phenotype (1, 10.0%). …”
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Examining the impact of probiotic Lactiplantibacillus pentosus 6MMI on inhibiting biofilm formation, adhesion, and virulence gene expression in Listeria monocytogenes ATCC 19115 by Behrooz Alizadeh Behbahani, Mostafa Rahmati-Joneidabad, Morteza Taki

“…In the next step of the study, the Gaussian Process Regression (GPR) model accurately predicted bile tolerance and acid parameters with a high R2 of 0.99 and minimal Mean Absolute Percentage Error (MAPE) values of 0.33 % and 0.21 %, respectively. …”
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Mitigation of Mycotoxin Content by a Single-Screw Extruder in Triticale (<i>x Triticosecale</i> Wittmack) by Breda Jakovac-Strajn, Janja Babič, Lato Pezo, Vojislav Banjac, Radmilo Čolović, Jovana Kos, Jelena Miljanić, Elizabet Janić Hajnal

“…According to the standard score, the optimum parameters for the reduction of the content of analysed mycotoxins were <i>M</i> = 24 g/100 g, <i>FR</i> = 25 kg/h, <i>SS</i> = 480 RPM, with a reduction of 3.80, 60.7, 61.5, 86.5, 47.7, and 55.9% for DON, 3-AcDON, 15-AcDON, HT-2, TEN, and AME, respectively. …”
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Diastolic dysfunction evaluation by cardiovascular magnetic resonance derived E, a, e’: Comparison to echocardiography by Jérôme Lamy, Jie Xiang, Nimish Shah, Jennifer M. Kwan, Yekaterina Kim, Krishna Upadhyaya, Samuel W. Reinhardt, Judith Meadows, Robert L. McNamara, Lauren A. Baldassarre, Dana C. Peters

“…The diagnostic accuracy of CMR for DD was determined.CMR derived E, A, E/A, e’ and E/e’ all correlated moderately to strongly with TTE, and more strongly when comparing studies performed closer in time (E: r = 0.68, E deceleration time: r = 0.82, A: r = 0.78, e’ r = 0.75, E/e’: r = 0.80, p = 0.001; LAVi: r = 0.79, p < 0.001; E/A: r = 0.82, p < 0.001, n = 14 within 45 days). …”
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Pharmacokinetics of Immediate and Sustained Release Cephalexin Administered by Different Routes to Llamas (Lama glama) by Verónica Kreil, Luis Ambros, Ana Paula Prados, Lisa Tarragona, Agustina Monfrinotti, Guillermo Bramuglia, Marcela Rebuelto

“…Cephalexin MIC90 values against staphylococci and E. coli were 1.0 and 8.0 μg/mL, respectively. Our results show that the immediate release formulation (10 mg/kg) would be effective for treating staphylococcal infections administered every 8 h (IM) or 12 h (SC), whereas the sustained release formulation (8 mg/kg) would require the IM or SC administration every 12 or 24 h, respectively.…”
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Machine learning-based prediction of in-hospital mortality for critically ill patients with sepsis-associated acute kidney injury by Tianyun Gao, Zhiqiang Nong, Yuzhen Luo, Manqiu Mo, Zhaoyan Chen, Zhenhua Yang, Ling Pan

“…Objectives This study aims to develop and validate a prediction model in-hospital mortality in critically ill patients with sepsis-associated acute kidney injury (SA-AKI) based on machine learning algorithms.Methods Patients who met the criteria for inclusion were identified in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database and divided according to the validation (n = 2440) and development (n = 9756, 80%) queues. Ensemble stepwise feature selection method was used to screen for effective features. …”
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Radiomics Features Based on MRI-ADC Maps of Patients with Breast Cancer: Relationship with Lesion Size, Features Stability, and Model Accuracy by Begumhan BAYSAL, Hakan BAYSAL, Mehmet Bilgin ESER, Mahmut Bilal DOGAN, Orhan ALIMOGLU

“…Feature selection was made with variance inflation factor (VIF, &lt;10) and least absolute shrinkage and selection operator regression. …”
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Dynamic assessment of long-term survival in survivors with stage III non-small cell lung cancer: a novel conditional survival model with a web-based calculator by Xiangdi Meng, Xiangdi Meng, Peihe Wang, Jie Liu, Daqing Sun, Zhuojun Ju, Yuanyuan Cai

“…The CS was calculated as CS(y|x) = OS(y + x)/OS(x), where OS(y + x) and OS(x) were the overall survival (OS) in the year (y + x) and year x, respectively, calculated by the Kaplan–Meier method. We used the least absolute shrinkage and selection operator (LASSO) regression to identify predictors and developed the CS-nomogram based on these predictors and the CS formula.ResultsThe CS analysis provided real-time updates on survival, with 5-year OS improving dynamically from 14.4 to 29.9%, 47.9, 66.0, and 80.8% (after 1–4 years of survival). …”
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Nineteen years retrospective analysis of epidemiology, antifungal resistance and a nomogram model for 30-day mortality in nosocomial candidemia patients by Zhang Dai, Xuhong Lan, Minjing Cai, Yunhui Liao, Jingwen Zhang, Naifang Ye, Xinxin Lu, Jiajia Wang, Yun Xiao, Yan Zhang, Yihui Yao, Xianming Liang

“…In the training set, the area under curve was 0.866 (95%CI: 0.817-0.916), the optimal cutoff value was 0.617, the sensitivity was 80% and the specificity was 80.4%. In the validation set, the area under curve was 0.808 (95%CI:0.737-0.970), the optimal cutoff value was 0.543. …”
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Development and approval of a Lasso score based on nutritional and inflammatory parameters to predict prognosis in patients with glioma by Huixian Li, Hui Hong, Jinling Zhang

“…The threshold probabilities for DCA at 1-, 3-, and 5-years post-surgery in the training and validation cohorts were 0.08~k0.74, 0.25~0.80, and 0.08~0.89, and 0.13~0.60, 0.28~0.81, and 0.25~0.88, respectively.ConclusionsA nomogram incorporating a Lasso score effectively predicted prognosis in glioma patients. …”
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Forecast for the zone of viticulture in European Russia under climate change by L. Yu. Novikova, P. V. Ozerski

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The Validation of a Novel, Sex-Specific LDL-Cholesterol Equation and the Friedewald, Sampson-NIH, and Extended-Martin–Hopkins Equations Against Direct Measurement in Korean Adults... by Hyun Suk Yang, Soo-Nyung Kim, Seungho Lee, Mina Hur

“…In the LDLc < 70 mg/dL group, the MAPE was as follows: SSLE (8.0%), Sampson-NIH (8.6%), ext-Martin–Hopkins (9.7%), and Friedewald (12.8%). …”
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An intraoperative nomogram for predicting secondary margin positivity in breast conserving surgery utilizing frozen section analysis by Cheng Li, Yan Jiang, Xumiao Wu, Yong Luo, Qi Li

“…This may reduce surgical complications and healthcare costs associated with multiple re-excisions and FSAs for recurrent positive margins.MethodsPatients were selected, divided into training and testing sets, and their data were collected. The Least Absolute Shrinkage and Selection Operator (LASSO) was used to identify significant variables from the training set for model building. …”
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