Aortic calcium score predicts early outcomes in aortoiliac revascularization by Adalberto Batalha Megale, Nelson Wolosker, Vitoria Magliari Kalil, João Mário Nigro, Carolina Sciammarella Wakisaka, Bianca Oberhuber Dias, Marcelo Passos Teivelis, Marcelo Assis Rocha, Cynthia de Almeida Mendes

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Pupillometry in the Emergency Department: A Tool for Predicting Patient Disposition by Hector Gonzalez Jr., Yanying Chen, Newton Addo, Debbie Y. Madhok

“…Traditional methods lack precision and consistency. Our goal was to evaluate the prognostic capability of the neurological pupil index (NPI) in predicting patient disposition from within the ED. …”
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Factors Predicting Uterine Rupture Following a Cesarean Section by Shehla Tabassum, Bushra Khan, Hina Zahra Qureshi, Humaira Imran

“…Objective: This study was conducted to evaluate factors that predict uterine rupture following a previous cesarean section. …”
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Analysis and prediction of atmospheric ozone concentrations using machine learning by Stephan Räss, Stephan Räss, Markus C. Leuenberger, Markus C. Leuenberger

“…As a first step, we used techniques like best subset selection to determine the measurement parameters that might be relevant for the prediction of ozone concentrations; in general, the parameters identified by these methods agree with atmospheric ozone chemistry. …”
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Can the Oxygen Saturation Index Predict Severe Bronchopulmonary Dysplasia? by Hulya Ozdemir, Sinem Gulcan Kersin, Asli Memisoglu, Ibrahim Kandemir, Hulya Selva Bilgen

“…Early detection of severe BPD can improve treatment outcomes. This study aims to evaluate the correlation between the oxygen saturation index (OSI) and severe BPD/death in preterm infants, with a focus on the OSI’s predictive value. …”
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Inflammatory marker comparison in childhood brucellosis: predicting osteoarticular involvement by Elif Böncüoğlu, Şadiye Kübra Tüter Öz, Zafer Bağcı

“…This study aimed to compare inflammatory markers in children diagnosed with brucellosis, distinguishing between those with and without osteoarticular involvement (OI). Methods. In this retrospective study, patients diagnosed with brucellosis from 1 month to 18 years of age were evaluated. …”
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TBESO-BP: an improved regression model for predicting subclinical mastitis by Kexin Han, Yongqiang Dai, Huan Liu, Junjie Hu, Leilei Liu, Zhihui Wang, Liping Wei

“…The primary objective is to discern models by exhibiting higher predictive accuracy and lower error values.ResultsThe evaluation of the TBESO-BP model in the test phase reveals a coefficient of determination R2 = 0.94, a Mean Absolute Error (MAE) of 2.07, and a Root Mean Square Error (RMSE) of 5.33. …”
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Impact of Selection Signature on Genomic Prediction and Heritability Estimation in Livestock by Hongzhi Zhang, Zhixu Pang, Wannian Wang, Liying Qiao, Wenzhong Liu

“…We evaluated the performance of two models: (1) selection-adjusted genomic best linear unbiased prediction (GBLUP-S), and (2) MAF-stratified selection-adjusted genomic best linear unbiased prediction (GBLUP-SMS). …”
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Role of conscious awareness and Big Five in predicting the digital addiction by Yıldız Erzincanli, Fatma Geçikli

“…In this context, the present study aims to determine the levels of conscious awareness and digital addiction among university students and to examine the predictive effect of conscious awareness levels and Big Five variables on predicting digital addiction behaviors.MethodsThe present study is designed to employ the survey method. …”
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Prediction of coalbed methane productivity based on neural network models by JIN Yi, ZHENG Chenhui, SONG Huibo, MA Jiaheng, YANG Yunhang, LIU Shunxi, ZHANG Kun, NI Xiaoming

“…Finally， according to the classification results， combined with the actual drainage data， the BP and LSTM neural network algorithms were used to predict the daily gas production of CBM wells.ResultsThe results show that： （1） Based on the grey correlation method model analysis， 10 parameters such as permeability， gas saturation and reservoir pressure gradient in the study area are the key factors affecting the gas production performance of coalbed methane； （2） Using fuzzy mathematics evaluation method to evaluate the enrichment of coalbed methane， the gas production effects of 34 wells in the study area is divided into three categories： favorable area， relatively favorable area and unfavorable area. （3）A coal reservoir daily gas production prediction model was established based on the LSTM algorithm， with a prediction error value between 4.06% and 14.79%， and the average error value of 11.09%. …”
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An Explainable Bayesian TimesNet for Probabilistic Groundwater Level Prediction by Zechen Peng, Shaoxing Mo, Alexander Y. Sun, Jichun Wu, Xiankui Zeng, Miao Lu, Xiaoqing Shi

“…Despite recent advances in machine learning (ML) methods for GWL prediction, further improvements may be made in uncertainty quantification and model interpretability. …”
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Albumin: a novel biomarker for predicting intraoperative hypothermia in HSCR by Xiaohui Huang, Mobai Ren, Junrong Pan, Ene Huang, Yanhong Li, Donghao Guo, Junjie Wang

“…Models were adjusted for covariates, and interaction terms were evaluated for albumin (ALB) and intraoperative hypothermia. …”
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Hyperspectral Imaging for Non-Destructive Moisture Prediction in Oat Seeds by Peng Zhang, Jiangping Liu

“…To further refine the predictive model, three feature selection methods—successive projections algorithm (SPA), competitive adaptive reweighted sampling (CARS), and principal component analysis (PCA)—were assessed. …”
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Brain Morphometry and Cognitive Features in the Prediction of Irritable Bowel Syndrome by Arvid Lundervold, Ben René Bjørsvik , Julie Billing , Birgitte Berentsen , Gülen Arslan Lied , Elisabeth K. Steinsvik , Trygve Hausken , Daniela M. Pfabigan , Astri J. Lundervold 

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The role of novel risk-scoring systems in predicting the efficacy of immunotherapy by Yu.V. Moskalenko

“…However, some patients resist ICIs, highlighting the need for novel risk-scoring systems to predict immunotherapy efficacy. Purpose – to evaluate the Lung Immune Prognostic Index (LIPI), Advanced Lung Cancer Inflammation Index (ALI), Patras Immunotherapy Score (PIOS), Prognostic Nutritional Index (PNI), and LEM score (Leukocytes, ECOG, Metastases) as predictors of ICI therapy efficacy in patients with mNSCLC. …”
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Prediction of acute pancreatitis severity based on early CT radiomics by Mingyao Qi, Chao Lu, Rao Dai, Jiulou Zhang, Hui Hu, Xiuhong Shan

“…Abstract Background This study aims to develop and validate an integrated predictive model combining CT radiomics and clinical parameters for early assessment of acute pancreatitis severity. …”
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Risk Prediction Models for Perioperative Hypothermia: A Systematic Review by Liu J, Liu F, Xu W, Du L, Li Y, Liang A, Li B, Zhang M

“…Due to its significant impact, this study systematically reviews and evaluates existing risk prediction models for perioperative hypothermia. …”
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Deformation prediction in innovative implant design with machine learning approaches by Mehmet Onur Yağır, Muhammed Fatih Pekşen, Şaduman Şen, Uğur Şen

“…Unlike classic implants, the sleeved implant is predicted to provide a more homogeneous distribution of chewing forces on the bone by reducing stress concentrations around the implant. …”
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Prediction of Recurrence of Atrial Fibrillation After Radiofrequency Ablation by Frailty by Ruochen Xu, Yan Dong, Nishant Yadav, Qiushi Chen, Kejiang Cao, Fengxiang Zhang

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Bayesian network for predicting mandibular third molar extraction difficulty by Tian Meng, Zhiyong Zhang, Xiao Zhang, Chao Zhang

“…Abstract Background This study aimed to establish a model for predicting the difficulty of mandibular third molar extraction based on a Bayesian network to meet following requirements: (1) analyse the interaction of the primary risk factors; (2) output quantitative difficulty-evaluation results based on the patient’s personal situation; and (3) identify key surgical points and propose surgical protocols to decrease complications. …”
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