Comparison of methods for tuning machine learning model hyper-parameters: with application to predicting high-need high-cost health care users by Christopher Meaney, Xuesong Wang, Jun Guan, Therese A. Stukel

“…Objective To compare several (nine) hyper-parameter optimization (HPO) methods, for tuning the hyper-parameters of an extreme gradient boosting model, with application to predicting high-need high-cost health care users. …”
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Impact of harmonization and oversampling methods on radiomics analysis of multi-center imbalanced datasets: application to PET-based prediction of lung cancer subtypes by Dongyang Du, Isaac Shiri, Fereshteh Yousefirizi, Mohammad R. Salmanpour, Jieqin Lv, Huiqin Wu, Wentao Zhu, Habib Zaidi, Lijun Lu, Arman Rahmim

“…Abstract Background Medical imaging data frequently encounter image-generation heterogeneity and class imbalance properties, challenging strong generalized predictive performances with data-driven machine-learning methods. …”
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Experimental Investigation of Land Mobile Prediction Methods and Modeling of Radio Planning Tool Parameters along Indian Rail Road Rural Zones by M. V. S. N. Prasad, P. K. Dalela, M. Chaitanya

“…In order to identify the suitable prediction methods for Indian rail road rural zones, train-based measurements were conducted in the northern and western rural zones along rail roads. …”
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A comparative study of regression methods to predict forest structure and canopy fuel variables from LiDAR full-waveform data by P. Crespo-Peremarch, L.A. Ruiz, A. Balaguer-Beser

“…Regression methods are widely employed in forestry to predict and map structure and canopy fuel variables. …”
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Determination of the sodium retardation factor using different methods: Analysis of their characteristics and impact on the solute movement prediction in a structured Brazilian soi... by Vanessa Godoy, Gian Franco Napa-García, Lázaro Zuquette

“…Its value can vary significantly depending on the method used for its determination. In this paper, the sodium Rd is experimentally determined using undisturbed sandy columns to compare four methods of Rd determination and assess the impact of the chosen method in the prediction of sodium movement. …”
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Prediction of key toxicity endpoints of AP-238 a new psychoactive substance for clinical toxicology and forensic purposes using in silico methods by Kamil Jurowski, Alicja Krośniak

“…A quantitative assessment of AP-238’s acute toxicity (AT) was performed by predicting theoretical LD50 values for both rats and mice across different administration routes using various in silico methods. …”
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Feature-based ensemble modeling for addressing diabetes data imbalance using the SMOTE, RUS, and random forest methods: a prediction study by Younseo Jang

“…Purpose This study developed and evaluated a feature-based ensemble model integrating the synthetic minority oversampling technique (SMOTE) and random undersampling (RUS) methods with a random forest approach to address class imbalance in machine learning for early diabetes detection, aiming to improve predictive performance. …”
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Prediction of the Calorific Value and Moisture Content of <i>Caragana korshinskii</i> Fuel Using Hyperspectral Imaging Technology and Various Stoichiometric Methods by Xuehong De, Haoming Li, Jianchao Zhang, Nanding Li, Huimeng Wan, Yanhua Ma

“…Finally, a comprehensive comparison of the modeling effectiveness of all methods was carried out, and the SNV-IRIV-PLSR modeling combination was the best for water content prediction, with its prediction set determination coefficient <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>(</mo><msubsup><mrow><mi>R</mi></mrow><mrow><mi>P</mi></mrow><mrow><mn>2</mn></mrow></msubsup><mo>)</mo></mrow></semantics></math></inline-formula>, root mean square error of prediction (RMSEP), and relative percentage deviation (RPD) of 0.9693, 0.2358, and 5.6792, respectively. …”
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Multicenter evaluation of predictive clinical and imaging factors for pathological response in non-small cell lung cancer patients treated with neoadjuvant chemotherapy and immune... by Mengzhe Zhang, Meng Yan, Zekun Li, Shuai Jiang, Zuo Liu, Pengpeng Zhang, Zhenfa Zhang

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Evaluating the potential of waist-to-BMI ratio, a body shape index, and other anthropometric parameters in predicting cardiovascular disease mortality: evidence from NHANES III by Thung-Lip Lee, Fang-Ju Lin, Chih-Fan Yeh, Yu-Chung Hsiao, Kai-Chien Yang, Chin-Feng Hsuan, Chau-Chung Wu

“…Abstract Background Anthropometric measures can be obtained easily and quickly and have the potential for prognostic stratification in the context of cardiovascular disease (CVD). This study evaluates the prognostic value of the waist-to-BMI ratio, a body shape index (ABSI), body roundness index (BRI), waist circumference (WC), and body mass index (BMI) for CVD mortality prediction in the general population, compared with the Framingham risk score (FRS). …”
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An Improved Decline Curve Analysis Method via Ensemble Learning for Shale Gas Reservoirs by Yu Zhou, Zaixun Gu, Changyu He, Junwen Yang, Jian Xiong

“…By combining the strengths of individual models, it offers a more robust and accurate prediction framework. We evaluated this method using data from 22 shale gas wells in region L, China, comparing it to six traditional DCA models, including Arps and the Logistic Growth Model (LGM). …”
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An Evaluation of Draminski Detector as an Early Detection Tool for Subclinical Mastitis in Dairy Cattle in Pondok Ranggon Farm by Herwin Pisestyani, Indra Permana, Chaerul Basri, Denny Widaya Lukman, Mirnawati Sudarwanto

“…This test method was also considered to have poor test performance in diagnosing cases of subclinical mastitis in dairy cattle with a sensitivity value of 3,5%, specificity 100%, positive predictive value 100%, negative predictive value 18,8%, estimated prevalence 2,9%, and the true prevalence was 81,7%. …”
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A Probability-Based Framework for Evaluating Slope Failure Under Rainfall Using Coupled Finite Element Analysis by Nadarajah Ravichandran, Tharshikka Vickneswaran

“…Deterministic limit equilibrium methods are typically used to evaluate the stability of slopes in terms of Factor of Safety (FoS), considering the worst-case scenario. …”
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Machine learning approaches for predicting the structural number of flexible pavements based on subgrade soil properties by Asadullah Ziar

“…Abstract This study presents a machine learning approach to predict the structural number of flexible pavements using subgrade soil properties and environmental conditions. …”
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Association between the nutritional inflammation index and mortality among patients with sepsis: insights from traditional methods and machine learning-based mortality prediction by Yuanshuo Ge, Ding Hu, Zhe Wang, Cheng Zhang

“…However, its prognostic significance in sepsis remains unclear. This study aims to evaluate the association between ANLR and mortality in sepsis patients using both traditional statistical methods and machine learning models. …”
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Study of aging life for EMU arresters based on aging tests and principal component analysis method by LI Ying, SONG Yanjun, XU Yuqi, LIU Kai, CHEN Kui, GAO Guoqiang

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Machine Learning-Driven Discovery and Evaluation of Antimicrobial Peptides from <i>Crassostrea gigas</i> Mucus Proteome by Jingchen Song, Kelin Liu, Xiaoyang Jin, Ke Huang, Shiwei Fu, Wenjie Yi, Yijie Cai, Ziniu Yu, Fan Mao, Yang Zhang

“…We conducted proteome sequencing of <i>C. gigas</i> mucous proteins, used the iAMPCN model for peptide activity prediction, and evaluated the antimicrobial, hemolytic, and cytotoxic capabilities of six peptides. …”
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Performance, emissions, and combustion analysis of catalytic hydrothermal liquefaction derived fuel from Arthrospira platensis in IC engines: A predictive approach using least squa... by Mozas Santhose Kumar J, Prakash Ramakrishnan, Padmanathan Panneerselvam

“…A multiple linear regression model, developed using the least squares method, predicted blend ratio (R² = 0.96, RMSE = 2.20) and load (R² = 0.9995, RMSE = 1.11) based on performance and emission parameters. …”
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Evaluation of postoperative delirium in cardiac surgery patients with the SDACS screening tool: a multicenter-multiphase study by Hosein Mahmoudi, Athanasios Chalkias, Ali Moradi, Seyed Tayeb Moradian, Seyed Mohammad Reza Amouzegar, Amir Vahedian-Azimi

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Developing a transparent reporting tool for AI-based diagnostic prediction models of disease and syndrome in Chinese medicine: a Delphi protocol by Jieyun Li, Jieyun Li, Wei Song Seetoh, Jiekee Lim, Jiekee Lim, Xin’ang Xiao, Xin’ang Xiao, Kehu Yang, Si Yong Yeo, Boyun Sun, Jinhua Liu, Zhaoxia Xu, Zhaoxia Xu, Linda L. D. Zhong

“…To address this gap, it is essential to establish a transparent and standardized reporting tool specifically designed for CM diagnostic and syndrome prediction models. This will enhance the transparency, reproducibility, and clinical relevance of research findings in this emerging field.MethodsThis study adopts a structured, multi-phase Delphi protocol. …”
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