A XGBoost-Based Prediction Method for Meat Sheep Transport Stress Using Wearable Photoelectric Sensors and Infrared Thermometry by Ruiqin Ma, Runqing Chen, Buwen Liang, Xinxing Li

“…Finally, machine learning algorithms such as Gaussian Naive Bayes (GaussianNB), Passive-Aggressive Aggregative Classifier (PAC), Nearest Centroid (NC), K-Nearest Neighbor Classification (KNN), Random Forest (RF), Support Vector Classification (SVC), Gradient Boosting Decision Tree (GBDT), and eXtreme Gradient Boosting (XGB) were established to predict the classification models of transportation stress in meat sheep. …”
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Predictive Value of Natriuretic Peptide Tests and Ischemia Modified Albumin Levels in the Diagnosis of Obstructive Sleep Apnoea Syndrome by Hamza Ogun, Eray Metin Güler, Beyza Nur Özkan, Muhammed Yunus Bektay, Abdullah Kansu, Ömer Faruk Çalım

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CO25 | Thromboinflammation and ros accumulation in individuals with high lipoprotein(a) levels

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Endothelial Activation and Stress Index Is Associated With Adverse Maternal and Perinatal Outcomes in Preeclampsia by Anna S. Scholz, Annabel Kussner, Michael Elsässer, Thomas Luft, Stephanie Wallwiener, Alexandra von Au

“…Therefore, we aimed to assess the predictive performance of EASIX for adverse maternal and perinatal outcomes in pregnancies with preeclampsia. …”
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Use of Machine Learning Algorithms to Predict Almen (Shot Peening) Intensity Values of Various Steel Materials by Murat İnce, Hatice Varol Özkavak

“…For all steel-group VSP samples, the highest CRS and hardness values were obtained at the 60 s −4 mm parameter. This paper aims to predict Almen intensity values using CRS, surface roughness, and hardness values from various steels. …”
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Outness predicts greater leukocyte telomere length in sexually minoritized men with HIV who use methamphetamine by Renessa S. Williams, Ariana Johnson, Michael Miller-Perusse, Annesa Flentje, Judy Moskowitz, Samantha E. Dilworth, Keith J. Horvath, Adam W. Carrico, Brad E. Aouizerat, Delaram Ghanooni

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Predictive evolution of metabolic phenotypes using model‐designed environments by Paula Jouhten, Dimitrios Konstantinidis, Filipa Pereira, Sergej Andrejev, Kristina Grkovska, Sandra Castillo, Payam Ghiachi, Gemma Beltran, Eivind Almaas, Albert Mas, Jonas Warringer, Ramon Gonzalez, Pilar Morales, Kiran R Patil

“…Overall, model‐designed selection environments open new opportunities for predictive evolution.…”
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Smart diabetes management: remote monitoring and predictive health insights by K.S. Smelyakov, I.A. Lurin, K.V. Misiura, A.S. Chupryna, T.V. Tyzhnenko, O.D. Dolhanenko, V.M. Repikhov

“…The article explores how modern technology is revolutionizing diabetes care by integrating conti­nuous glucose monitoring (CGM), predictive analytics, and remote healthcare solutions. …”
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Predictive performance of stress hyperglycemia ratio for poor prognosis in critically ill patients: a systematic review and dose–response meta-analysis by Lili Chen, Xiaoxue Zeng, Wenjing Zou, Meng Chen, Ya Fan, Ping Huang

“…As a non-invasive and easily obtainable indicator, there is no systematic evidence-based medical evidence to support the value of SHR in predicting the poor prognosis of critically ill patients at present. …”
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Flow Accelerated Corrosion Prediction in High Pressure Economizer of a Heat Recovery Steam Generator by Phuris Khunphakdee, Kiattikhoon Phuakpunk, Benjapon Chalermsinsuwan

“…This recirculation forced the flow in the remaining area to accelerate, causing higher wall shear stresses on the side opposite the recirculation. As high shear stresses correlate with the locations where the flow accelerated corrosion occurs severely in practice, the Chilton-Colburn analogy was applied for FAC rate prediction. …”
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Genetic Programming-Based Prediction Model for Microseismic Data by Man Wang, Hongwei Zhou, Dongming Zhang, Yingwei Wang, Weihang Du, Beichen Yu

“…The results showed that the actual seismic and energy data of the working faces exhibited good agreement with those predicted by the prediction formulas. The high energy and seismic distribution were caused by the mining stress at the edge of working faces due to the excavation and unloading effect of the surface, and the energy and seismic evolution predicted by GP could also show this phenomenon well.…”
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Genetically predicted cortisol levels and risk of venous thromboembolism. by Elias Allara, Wei-Hsuan Lee, Stephen Burgess, INVENT consortium, Susanna C Larsson

“…<h4>Introduction</h4>In observational studies, venous thromboembolism (VTE) has been associated with Cushing's syndrome and with persistent mental stress, two conditions associated with higher cortisol levels. …”
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Correction for post-traumatic stress disorder can be predicted in hospitalized blunt trauma patients using a simple screening tool

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USING THE METHODS OF SYSTEMS BIOLOGY FOR PREDICTING PERSPECTIVE TARGET GENES TO SELECT C3 AND C4 CEREALS FOR OXIDATIVE STRESS RESISTANCE by A. V. Doroshkov, A. V. Bobrovskikh

“…Cells produce ROS during normal metabolism reactions, but ROS production increases under stressful conditions. Improving the antioxidant system in cultivated plants will increase their tolerance to abiotic stresses, such as salinity, drought and cold. …”
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Predicting potato plant vigor from the seed tuber properties by Elisa Atza, Rob Klooster, Falko Hofstra, Frank van der Werff, Hans van Doorn, Neil Budko

“…At the same time, for the variety that appeared to be less sensitive to environmental stresses, we obtained cross-field and cross-year vigor predictions correlating up to $$80\%$$ with the measurements. …”
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PREDICTIVE VALUE OF ECHOCARDIOGRAPHY IN POST MYOCARDIAL INFARCTION SETTING. PART 2 by P. V. Krikunov, Yu. A. Vasyuk, O. V. Krikunova

“…It was shown, that for prediction related data acquisition, it is possible to apply multiple echocardiographic parameters, such as the volumes and ejection fraction of the left ventricle, wall motion index, left atrium volume, and existence of atrial regurgitation. …”
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PREDICTIVE VALUE OF ECHOCARDIOGRAPHY IN POST MYOCARDIAL INFARCTION SETTING. PART 1 by P. V. Krikunov, Yu. A. Vasyuk, O. V. Krikunova

“…It was shown, that for prediction related data acquisition, it is possible to apply multiple echocardiographic parameters, such as the volumes and ejection fraction of the left ventricle, wall motion index, left atrium volume, and existence of atrial regurgitation. …”
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Risk prediction models for stress urinary incontinence after pelvic organ prolapse (POP) surgery: a systematic review and meta-analysis by Bi Jun Yu, Hao Chong He, Li Wang, Han Mei Shao, Ying Min Liu, Xiao Ying Yan, Jian Liu

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Developing a geomechanical model to predict breakdown pressure in a vertical borehole using failure analysis: a case study by Majid Jamshidian, Mostafa Mansuri Zadeh, Omid Mohammadzadeh, Mohammad Abdideh

“…Four failure criteria, namely Mohr–Coulomb, 2D Hoek–Brown, Hubbert-Willis and 3D Mogi-Coulomb were used to obtain the breakdown pressure for the target reservoir. Based on the prediction results of these failure criteria, it was obtained that 2D Hoek–Brown, Hubbert-Willis, and 3D Mogi-Coulomb criteria resulted in seemingly unrealistic breakdown pressures with respect to the minimum horizontal stress gradient. …”
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Genetically Predict Diet‐derived Antioxidants and Risk of Neurodegenerative Diseases Among Individuals of European Descent: A Mendelian Randomization Study by Qing‐Qing Duan, Wei‐Ming Su, Xiao‐Jing Gu, Jiang Long, Zheng Jiang, Kang‐Fu Yin, Wei‐Chen Cai, Bei Cao, Li‐Yi Chi, Xia Gao, Ju‐Rong Li, Yong‐Ping Chen

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