The clinical prediction model to distinguish between colonization and infection by Klebsiella pneumoniae by Xiaoyu Zhang, Xifan Zhang, Deng Zhang, Jing Xu, Jingping Zhang, Xin Zhang

“…ObjectiveTo develop a machine learning-based prediction model to assist clinicians in accurately determining whether the detection of Klebsiella pneumoniae (KP) in sputum samples indicates an infection, facilitating timely diagnosis and treatment.Research methodsA retrospective analysis was conducted on 8,318 patients with KP cultures admitted to a tertiary hospital in Northeast China from January 2019 to December 2023. …”
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Enhancing Genomic Prediction Accuracy of Reproduction Traits in Rongchang Pigs Through Machine Learning by Junge Wang, Jie Chai, Li Chen, Tinghuan Zhang, Xi Long, Shuqi Diao, Dong Chen, Zongyi Guo, Guoqing Tang, Pingxian Wu

“…The methods’ efficacy was evaluated using fivefold cross-validation and independent tests. …”
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Feature Engineering for the Prediction of Scoliosis in 5q‐Spinal Muscular Atrophy by Tu‐Lan Vu‐Han, Vikram Sunkara, Rodrigo Bermudez‐Schettino, Jakob Schwechten, Robin Runge, Carsten Perka, Tobias Winkler, Sebastian Pokutta, Claudia Weiß, Matthias Pumberger

“…To test the predictive performance of the selected features, we trained a Random Forest Classifier and evaluated model performance using standard metrics. …”
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Aircraft Multi-stage Altitude Prediction Under Satellite Signal Loss by Mengchan HUANG, Qiang MIAO

“…Several comparative experiments are designed to comprehensively evaluate the LTCA–TCN altitude prediction algorithm proposed herein. …”
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An anoikis-related signature predicts prognosis and immunotherapy response in gastrointestinal cancers by Ruyi Liu, Ruyi Liu, Ruyi Liu, Ruyi Liu, Ruyi Liu, Yuchen Liu, Yuchen Liu, Yuchen Liu, Yuchen Liu, Yuchen Liu, Weicheng Huang, Weicheng Huang, Weicheng Huang, Weicheng Huang, Weicheng Huang, Pengxiang Chen, Pengxiang Chen, Pengxiang Chen, Pengxiang Chen, Pengxiang Chen, Yufeng Cheng, Yufeng Cheng, Yufeng Cheng, Yufeng Cheng, Yufeng Cheng

“…It demonstrated the robust predictive capability for the prognosis of patients with GI cancers. …”
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Predicting Insemination Outcome in Holstein Dairy Cattle using Deep Learning by Mohammad Alishahi, Mahdi Ravakhah

“…In the problem of predicting the results of artificial insemination of livestock, the presented LSTM neural network model shows the best performance based on the stated evaluation criteria, and then the XGBoost-based classifier has better performance than MLP.…”
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AI-Cirrhosis-ECG (ACE) score for predicting decompensation and liver outcomes by Joseph C. Ahn, Puru Rattan, Patrick Starlinger, Adrià Juanola, Maria José Moreta, Jordi Colmenero, Bashar Aqel, Andrew P. Keaveny, Aidan F. Mullan, Kan Liu, Zachi I. Attia, Alina M. Allen, Paul A. Friedman, Vijay H. Shah, Peter A. Noseworthy, Julie K. Heimbach, Patrick S. Kamath, Pere Gines, Douglas A. Simonetto

“…We evaluated whether the deep learning-based AI-Cirrhosis-ECG (ACE) score could detect hepatic decompensation and predict clinical outcomes in cirrhosis. …”
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Development and validation of a risk assessment model for predicting the failure of early medical abortions: A clinical prediction model study based on a systematic review and meta... by An-Hao Liu, Bin Xu, Xiu-Wen Li, Yue-Wen Yu, Hui-Xin Guan, Xiao-Lu Sun, Yan-Zhen Lin, Li-Li Zhang, Xian-Di Zhuo, Jia Li, Wen-Qun Chen, Wen-Feng Hu, Ming-Zhu Ye, Xiu-Min Huang, Xun Chen

“…<h4>Objective</h4>As the first model in predicting the failure of early medical abortion (EMA) was inefficient, this study aims to develop and validate a risk assessment model for predicting the failure of EMAs more accurately in a clinical setting.…”
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Evaluating the concordance between Vesical Imaging Reporting and Data System scores and bladder tumor histopathology by Hasan Gungor, Ahmet Camtosun, Ibrahim Topcu, Leyla Karaca

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Evaluating the Relationship between Physiological Parameters and Performance of Female Swimmers in the 200 m Individual Medley by Rajarshi Gayen, Sandhya Tiwari, Sandeep Tiwari

“…Multiple linear regression was used for evaluating the contribution of identified physiological variables and construction of predictive model. …”
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Estimating Models and Evaluating their Efficiency under Multicollinearity in Multiple Linear Regression: A Comparative Study by Saman Hussein Mahmood

“…The research aims to diagnose the multicollinearity problem between explanatory variables in the linear regression model and identifying the variables causing this problem based on the variance inflation factor (VIF), then estimation and evaluate the performance of three alternative methods, which are Ridge regression, principal components analysis, and Feedforward Neural Networks (FFNN) models with one and two hidden layers and application of the models to compressive strength data for high-performance concrete. …”
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Influencing factors of cross screening rate and its intelligent prediction model by Lala ZHAO, Feng XU, Chenlong DUAN, Chenhao GUO, Wei WANG, Haishen JIANG, Jinpeng QIAO

“…Based on the machine learning method, the intelligent prediction model of the screening rate of the cross screen is studied. …”
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Aspects correlates with Scandinavian Stroke Scale for predicting early neurological impairment by Gustavo José Luvizutto, Maicon Gonçalves Gabriel, Gabriel Pereira Braga, Thiago Dias Fernandes, Luiz Antônio de Lima Resende, Octávio Marques Pontes Neto, Rodrigo Bazan

“…Method 59 patients with a first acute ischemic stroke were evaluated. …”
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Storage Life Prediction Based on Kernel Path Classification and Estimation Model by PAN Yuxiong, ZHOU Guifa, WANG Xu

“…Evaluated results of remaining storage life for a type electromechanical product show that KPACE model has higher prediction accuracy and smaller variance than that of the statistic model for small specimen condition.…”
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PRECISION AND STABILITY OF THE PREDICTION FORMULA FOR BURST STRENGTH OF PRESSURE-BEARING CYLINDER by LIU Cen, YANG Fan, WU SengLin, HONG Kai, ZHANG Shu, LIU XiaoNing

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Predicting wildlife corridors for multiple species in an East African ungulate community. by Jason Riggio, Katie Foreman, Ethan Freedman, Becky Gottlieb, David Hendler, Danielle Radomille, Ryan Rodriguez, Thomas Yamashita, John Kioko, Christian Kiffner

“…To model robust corridors for multiple species and simultaneously evaluate the impact of methodological choices, we develop a multi-method approach to delineate corridors that effectively capture movement of multiple wildlife species, while limiting the area required. …”
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Contextual bandits to increase user prediction accuracy in movie recommendation system by Chen Yizhe

“…This paper suggests a possible selection of CMAB for recommendation systems to alleviate the cold start problem and estimates the tuned parameters for the MovieLens dataset. The evaluation metric in this paper provides a possible method of analyzing the general performance of a hybrid recommendation system, instead of adopting multiple evaluation metrics respectively, these metrics also provide estimates of the optimal value of parameters.…”
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A Supervised Approach to Predict the Hierarchical Structure of Conversation Threads for Comments by A. Balali, H. Faili, M. Asadpour

“…Then, we use supervised learning to combine these features. The proposed method is evaluated on five different datasets. The accuracy of the proposed method is compared with baselines. …”
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Presenting a prediction model for HELLP syndrome through data mining by Boshra Farajollahi, Mohammadjavad Sayadi, Mostafa Langarizadeh, Ladan Ajori

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Activity prediction of anti-cancer drug candidate ERα inhibitor by XIA Yulan, XIE Jiming, WANG Yajing, LU Mengyuan, WANG Jinrui, QIN Yaqin

“…Finally, the prediction effect of model is analyzed and evaluated. …”
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