An Approach to, and Tool for, Predicting the Time Course of an Infectious Disease Outbreak as a Function of Behavioral Interventions by Abebe HT, Siraj A, Berhane K, Siraj D, Van Breukelen GJ

“…However, most decisions rely on expert opinions rather than robust epidemic model outputs. Implementing epidemic models can be challenging without a strong background in statistical modeling.Methods: This paper presents a simple, user-friendly tool in MATLAB to predict the time course of an infectious disease outbreak using various modified epidemic models. …”
Get full text

Baird´s tapir: predicting patterns of crop damage surrounding the Calakmul Biosphere Reserve, Campeche, Mexico by Isabel Serrano-Mac-Gregor, Rafael Reyna-Hurtado, Dolores Molina-Rosales, Eduardo Naranjo-Piñera

Get full text

Introduction to deep learning methods for multi‐species predictions by Yuqing Hu, Sara Si‐Moussi, Wilfried Thuiller

“…Additionally, we showcased how interpretability tools can illuminate community structure as seen by deep learning models. Deep learning models offer a broad array of features for predicting entire species communities. …”
Get full text

Comparison of Single-Trait and Multi-Trait GBLUP Models for Genomic Prediction in Red Clover by Johanna Osterman, Lucia Gutiérrez, Linda Öhlund, Rodomiro Ortiz, Cecilia Hammenhag, David Parsons, Mulatu Geleta

Subjects: “…longitudinal genomic prediction model…”
Get full text

Integrating structured and unstructured data for predicting emergency severity: an association and predictive study using transformer-based natural language processing models by Xingyu Zhang, Yanshan Wang, Yun Jiang, Charissa B. Pacella, Wenbin Zhang

Subjects: Get full text

Predicting outcomes of expectant and medical management in early pregnancy miscarriage using machine learning to develop and validate multivariable clinical prediction models by Sughashini Murugesu, Kristofer Linton-Reid, Emily Braun, Jennifer Barcroft, Nina Cooper, Margaret Pikovsky, Alex Novak, Nina Parker, Catriona Stalder, Maya Al-Memar, Srdjan Saso, Eric O. Aboagye, Tom Bourne

“…Abstract Objective To determine whether readily available patient, ultrasound and treatment outcome data can be used to develop, validate and externally test two machine learning (ML) models for predicting the success of expectant and medical management of miscarriage respectively. …”
Get full text

Predictive value of near-term prediction models for severe immune-related adverse events in malignant tumor PD-1 inhibitor therapy by Yunyi Du, Ying Zhang, Wenqi Zhao, Yuexiang Zhang, Fei Su, Xiaoling Zhang, Weiling Li, Wenqing Hu, Yongai Li, Jun Zhao

Subjects: Get full text

Variability in performance of genetic-enhanced DXA-BMD prediction models across diverse ethnic and geographic populations: A risk prediction study. by Yong Liu, Xiang-He Meng, Chong Wu, Kuan-Jui Su, Anqi Liu, Qing Tian, Lan-Juan Zhao, Chuan Qiu, Zhe Luo, Martha I Gonzalez-Ramirez, Hui Shen, Hong-Mei Xiao, Hong-Wen Deng

“…This study aims to develop BMD prediction models using data from the UK Biobank (UKBB) and test their performance across different ethnic and geographical populations.…”
Get full text

Emulsion stability prediction tool by Nor H. Halim, Sai R. Panuganti, Sanjay Misra, Jamal M.B.M. Ibrahim

“…A faster and safer alternative is by running a mathematical model. However, because of the complexity of emulsion system, an equation from first principles for predicting emulsion stability is not available even with such vast work in the literature. …”
Get full text

Predicting post-hospital lethality in males and females with acute coronary syndrome by R. T. Saygitov, M. G. Glezer, D. P. Sementsov, I. N. Sokolova, N. A. Malygina

“…This predicted risk gives a chance to divide patients into risk groups - with minimal (lethality < 1 %) to maximal (lethality > 30 %) risk, as well as to predict possible time of death. …”
Get full text

Modeling Population Growth in R with the biogrowth Package by Alberto Garre, Jeroen Koomen, Heidy M. W. den Besten, Marcel H. Zwietering

Subjects: “…kinetic modelling…”
Get full text

Predictive features analysis and nomogram construction for predicting depression in elderly patients by Wei Lin, Zijun Zhao, Yingshan Yu, Hongbin Chen

Subjects: Get full text

The prediction of the effects of non-isothermal molding/reprocessing on the crystallinity and mechanical properties of PEEK and CF/PEEK by Pingping Xiong, Yangwei Zhou, Laishui Zhou, Zhenchao Qi

“…In addition, mathematical models for predicting the crystallinity and mechanical properties of PEEK and CF/PEEK were established, and the accuracy of the models was verified by a series of experiments. …”
Get full text

Future Prediction for Tax Complaints to Turkish Ombudsman by Models from Polynomial Regression and Parametric Distribution by Mehmet Niyazi Çankaya, Murat Aydın

“…The maximum values are around $700$ and $800$ which can be regarded as future prediction because the distance among observations is taken into account by models from polynomial regression and parametric distribution. …”
Get full text

Machine Learning Radiomics for Predicting Response to MR-Guided Radiotherapy in Unresectable Hepatocellular Carcinoma: A Multicenter Cohort Study by Su K, Liu X, Zeng YC, Xu J, Li H, Wang H, Du S, Wang H, Yue J, Yin Y, Li Z

“…The machine learning radiomics model developed in this study could accurately predict the response of radiotherapy-treated inoperable HCC.Keywords: machine learning models, radiomics, radiotherapy, hepatocellular carcinoma…”
Get full text

Prediction of vaccination coverage levels in populations with increasing levels of heterogeneity by Fan Bai

“…Heterogeneity of population is a key factor in modelling the transmission of disease among the population and has huge impact on the outcome of the transmission. …”
Get full text

Prediction and design of thermostable proteins with a desired melting temperature by Purva Tijare, Nishant Kumar, Gajendra P. S. Raghava

Subjects: Get full text

Downscaling for Rainfall Prediction in the Aburrá River Valley and its Supplying Watersheds in Antioquia (Colombia) Using Non-Homogeneous Hidden Markov Models by Diego Felipe Osorio Giraldo, Luis Fernando Carvajal Serna, Juli´án David Rojo Hernández

Get full text

Benchmarking of feed-forward neural network models for genomic prediction of quantitative traits in pigs by Junjian Wang, Francesco Tiezzi, Yijian Huang, Christian Maltecca, Jicai Jiang

“…These advanced modeling capabilities make them promising candidates for genomic prediction by potentially capturing the intricate relationships between genetic variants and phenotypes. …”
Get full text

Comparative Analysis of ARIMA and lSTM Predictive Models: Evidence from Russian Stocks by A. V. Alzheev, R. A. Kochkarov

Subjects: Get full text