Impact of climate change on the distribution of Isaria cicadaeMiquel in China: predictions based on the MaxEnt model by Zhipeng He, Habib Ali, Junhao Wu, Zhiqian Liu, Xinju Wei, Zhihang Zhuo

“…Understanding its potential distribution is essential for promoting sustainable harvesting practices.MethodsThis study utilizes the MaxEnt model, combined with known distribution records and 22 environmental variables, to predict the potential distribution of I. cicadae under three representative emission scenarios (CMIP6: SSP1-2.6, SSP2-4.5, and SSP5-8.5) for the 2050s and 2070s.ResultsThe analysis identifies seven key environmental variables influencing the habitat suitability of I. cicadae: the mean temperature of the driest quarter (bio09), the mean temperature of the wettest quarter (bio08), precipitation in the wettest month (bio16), the mean diurnal range (bio02), isothermality (bio03), elevation, and slope. …”
Get full text

Bi-GRCN: A Spatio-Temporal Traffic Flow Prediction Model Based on Graph Neural Network by Wenhao Jiang, Yunpeng Xiao, Yanbing Liu, Qilie Liu, Zheng Li

“…The experimental results show that the model can not only effectively predict the short-term traffic flow but also get a good prediction effect in the medium- and long-term traffic flow prediction.…”
Get full text

Overcoming Missing Data: Accurately Predicting Cardiovascular Risk in Type 2 Diabetes, A Systematic Review by Wenhui Ren, Keyu Fan, Zheng Liu, Yanqiu Wu, Haiyan An, Huixin Liu

“…ABSTRACT Understanding is limited regarding strategies for addressing missing value when developing and validating models to predict cardiovascular disease (CVD) in type 2 diabetes mellitus (T2DM). …”
Get full text

Predicted Anchor Region Proposal with Balanced Feature Pyramid for License Plate Detection in Traffic Scene Images by Hoanh Nguyen

“…Furthermore, this paper designs a multiscale region proposal network with a novel predicted location anchor scheme to generate high-quality proposals. …”
Get full text

Comparison between Satellite Water Vapour Observations and Atmospheric Models’ Predictions of the Upper Tropospheric Thermal Radiation by J. R. Dim, T. Y. Nakajima, T. Takamura, N. Kikuchi

Get full text

Predicting ash content and water content in coal using full infrared spectra and machine learning models by Suprapto Suprapto, Antin Wahyuningtyas, Kartika Anoraga Madurani, Yatim Lailun Ni'mah

“…The aim of this study was to predict ash and water contents in coal samples using machine learning regression techniques, specifically LassoCV, RidgeCV, ElasticNetCV and LassoLarsCV. …”
Get full text

Biomarkers for Predicting Left Atrial or Left Atrial Appendage Thrombus in Anticoagulated Patients with Nonvalvular Atrial Fibrillation by Xue Zhou, Zuolan Wang, Shuang Dou, Kangyin Chen, Enzhao Liu, Tong Liu, Guangping Li, Jingjin Che

Get full text

A novel perspective on survival prediction for AML patients: Integration of machine learning in SEER database applications by Zheng-yi Jia, Maierbiya Abulimiti, Yun Wu, Li-na Ma, Xiao-yu Li, Jie Wang

Subjects: Get full text

Association of HLA-B27 Gene and Rheumatoid Arthritis: Analysis of Potential Role as a Predictive Biomarker by Karzan Ghafur Khidhir, Baban Ahmad, Dana Khdr Sabir

Get full text

Evidence-based dust exposure prediction and/or control tools in occupational settings: A scoping review protocol. by Gebisa Guyasa Kabito, Yonatal Tefera, Chandnee Ramkissoon, Sharyn Gaskin

“…In recent decades, evidence-based tools supporting exposure modelling and control banding have been developed to aid in predicting and/or controlling occupational exposure to various contaminants. …”
Get full text

Prediction Study on PCI Failure of Reactor Fuel Based on a Radial Basis Function Neural Network by Xinyu Wei, Jiashuang Wan, Fuyu Zhao

“…Pellet-clad interaction (PCI) is one of the major issues in fuel rod design and reactor core operation in water cooled reactors. The prediction of fuel rod failure by PCI is studied in this paper by the method of radial basis function neural network (RBFNN). …”
Get full text

Actors influencing cancer-related fatigue and the construction of a risk prediction model in lung cancer patients by Mei-Ning Zhang, Yi-Chen Zhou, Zhu Zeng, Cun-Liang Zeng, Bo-Tao Hou, Gui-Rong Wu, Qiao Jiao, Dai-Yuan Ma

Subjects: Get full text

Predictive Analysis of Economic Chaotic Time Series Based on Chaotic Genetics Combined with Fuzzy Decision Algorithm by Xiuge Tan

“…The phase space of its reconstructed chaotic attractor has high-precision predictability and can find orderly processes from changeable economic results, which in turn can be used to analyze and predict the complex economic chaotic time series. …”
Get full text

Predicting Crash Frequency for Urban Expressway considering Collision Types Using Real-Time Traffic Data by Hui Zhang, Siyao Li, Chaozhong Wu, Qi Zhang, Yafen Wang

“…Current studies on traffic crash prediction mainly focus on the crash frequency and crash severity of freeways or arterials. …”
Get full text

Body Fat Equations and Electrical Bioimpedance Values in Prediction of Cardiovascular Risk Factors in Eutrophic and Overweight Adolescents by Franciane Rocha Faria, Eliane Rodrigues Faria, Roberta Stofeles Cecon, Djalma Adão Barbosa Júnior, Sylvia do Carmo Castro Franceschini, Maria do Carmo Gouveia Peluzio, Andréia Queiroz Ribeiro, Pedro Israel Cabral Lira, Paulo Roberto Cecon, Silvia Eloiza Priore

“…The aim of this study was to analyze body fat anthropometric equations and electrical bioimpedance analysis (BIA) in the prediction of cardiovascular risk factors in eutrophic and overweight adolescents. 210 adolescents were divided into eutrophic group (G1) and overweight group (G2). …”
Get full text

Innovative Assessment of Crohn’s Disease: An Activity Prediction Tool Combining Laboratory Data and Imaging [Letter] by Wang F, Jiang Q, He P

Get full text

Short-Term Power Prediction of Building Integrated Photovoltaic (BIPV) System Based on Machine Learning Algorithms by R. Kabilan, V. Chandran, J. Yogapriya, Alagar Karthick, Priyesh P. Gandhi, V. Mohanavel, Robbi Rahim, S. Manoharan

“…The proposed prediction methodology comprises a data quality stage, machine learning algorithm, weather clustering assessment, and an accuracy assessment. …”
Get full text

Improving stroke risk prediction by integrating XGBoost, optimized principal component analysis, and explainable artificial intelligence by Lesia Mochurad, Viktoriia Babii, Yuliia Boliubash, Yulianna Mochurad

“…To improve stroke risk prediction models in terms of efficiency and interpretability, we propose to integrate modern machine learning algorithms and data dimensionality reduction methods, in particular XGBoost and optimized principal component analysis (PCA), which provide data structuring and increase processing speed, especially for large datasets. …”
Get full text

New Parameters for Impedance–pH Monitoring in Diagnosing Gastroesophageal Reflux Disease and Predicting its Severity by O. A. Storonova, A. S. Trukhmanov, A. A. Makushina, A. V. Paraskevova, V. T. Ivashkin

Get full text

Simplified Outcome Prediction in Patients Undergoing Transcatheter Tricuspid Valve Intervention by Survival Tree-Based Modelling by Vera Fortmeier, MD, Mark Lachmann, MD, Lukas Stolz, MD, Jennifer von Stein, MD, Karl-Philipp Rommel, MD, Mohammad Kassar, MD, Muhammed Gerçek, MD, Anne R. Schöber, MD, Thomas J. Stocker, MD, Hazem Omran, MD, Michelle Fett, Jule Tervooren, Maria I. Körber, MD, Amelie Hesse, Gerhard Harmsen, PhD, Kai Peter Friedrichs, MD, Shinsuke Yuasa, MD, PhD, Tanja K. Rudolph, MD, Michael Joner, MD, Roman Pfister, MD, Stephan Baldus, MD, Karl-Ludwig Laugwitz, MD, Stephan Windecker, MD, Fabien Praz, MD, Philipp Lurz, MD, Jörg Hausleiter, MD, Volker Rudolph, MD

“…Results: Following univariate regression analysis to pre-select candidate variables for 2-year mortality prediction, a survival tree-based model was constructed using 4 key parameters. …”
Get full text