Neonatal apnea and hypopnea prediction in infants with Robin sequence with neural additive models for time series. by Julius Vetter, Kathleen Lim, Tjeerd M H Dijkstra, Peter A Dargaville, Oliver Kohlbacher, Jakob H Macke, Christian F Poets

“…Our prediction model presents a step towards an automatic prediction of neonatal apneas and hypopneas in infants at risk for upper airway obstruction. …”
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Reporting and Performance of Hepatocellular Carcinoma Risk Prediction Models: Based on TRIPOD Statement and Meta-Analysis by Liuqing Yang, Qiang Wang, Tingting Cui, Jinxin Huang, Hui Jin

“…The performance of risk prediction models for hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB) was uncertain. …”
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Comparative Analysis of Artificial Neural Networks with Classical Regression Models for Predicting Dissolved Oxygen in Water by Ana Ivette Jater Ruiz, Francisco Primero Primero, Roberto Alejo Eleuterio, Francisco Javier Illescas Martínez, Federico Del Razo López, Everardo Granda

“…In this study, we evaluate the effectiveness of Artificial Neural Networks (ANNs) in predicting DO levels by comparing seven different ANN architectures to nine classical regression models. …”
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Prognostic models for predicting in-hospital paediatric mortality in resource-limited countries: a systematic review by Morris Ogero, Samuel Akech, Mike English, Jalemba Aluvaala, Ambrose Agweyu, Lucas Malla, Rachel Jelagat Sarguta, Nelson Owuor Onyango

“…Objectives To identify and appraise the methodological rigour of multivariable prognostic models predicting in-hospital paediatric mortality in low-income and middle-income countries (LMICs).Design Systematic review of peer-reviewed journals.Data sources MEDLINE, CINAHL, Google Scholar and Web of Science electronic databases since inception to August 2019.Eligibility criteria We included model development studies predicting in-hospital paediatric mortality in LMIC.Data extraction and synthesis This systematic review followed the Checklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies framework. …”
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Comparative analysis of machine learning models for predicting water quality index in Dhaka’s rivers of Bangladesh by Mosaraf Hosan Nishat, Md. Habibur Rahman Bejoy Khan, Tahmeed Ahmed, Syed Nahin Hossain, Amimul Ahsan, M. M. El-Sergany, Md. Shafiquzzaman, Monzur Alam Imteaz, Mohammad T. Alresheedi

“…To our knowledge, this is the first study to apply such a comprehensive range of ML models to predict the WQI of Dhaka’s four major rivers. …”
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An algorithm to assess importance of predictors in systematic reviews of prediction models: a case study with simulations by Ruohua Yan, Chen Wang, Chao Zhang, Xiaohang Liu, Dong Zhang, Xiaoxia Peng

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Adapting Machine Learning Models for Indoor Temperature Prediction from Kuwait to the French Riviera Climate by Sedaghat Ahmad, Nazififard Mohammad, Franquet Erwin, Kalbasi Rasool, Mostafaeipour Ali

“…A total of nineteen regression (ML) models are examined. The Matern 5/2 Gaussian process regression model has done somewhat better at modeling interior temperature; all models are shown to function well. …”
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Developing multifactorial dementia prediction models using clinical variables from cohorts in the US and Australia by Caitlin A. Finney, David A. Brown, Artur Shvetcov

“…Abstract Existing dementia prediction models using non-neuroimaging clinical measures have been limited in their ability to identify disease. …”
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Large language models predict cognition and education close to or better than genomics or expert assessment by Tobias Wolfram

“…These findings show that recent advances in large language models and machine learning equip behavioural scientists with tools for prediction of psycho-social features.…”
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Development and Verification of Prognostic Prediction Models for Patients with Brain Trauma Based on Coagulation Function Indexes by Lanjuan Xu, Tingting An, Chengjian Li, Xin Shi, Bo Yang

“…To assess the effect of adding coagulation indices to the currently existing prognostic prediction models of traumatic brain injury (TBI) in the prediction of outcome. …”
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From Prediction to Explanation: Using Explainable AI to Understand Satellite-Based Riot Forecasting Models by Scott Warnke, Daniel Runfola

“…This study investigates the application of explainable AI (XAI) techniques to understand the deep learning models used for predicting urban conflict from satellite imagery. …”
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A Comparative Analysis of the Effectiveness of Multiple Models for Predicting Heart Failure using Data Mining by Ahmed Sami Jaddoa, Juliet Kadum, Amaal Kadum

“…For forecasting, decision-making, and disease prediction, DM technologies are essential. This research predicts heart disease using DM algorithms. …”
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COMPARISON LINEAR REGRESSION AND RANDOM FOREST MODELS FOR PREDICTION OF UNDERGROUND DROUGHT LEVELS IN FOREST FIRES by Nur Alamsyah, Budiman Budiman, Titan Parama Yoga, R Yadi Rakhman Alamsyah

“…This research aims to develop a prediction model for underground drought levels in the context of forest fires using machine learning techniques. …”
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Individualized epidemic spreading models predict epilepsy surgery outcomes: A pseudo-prospective study by Ana P. Millán, Elisabeth C. W. van Straaten, Cornelis J. Stam, Ida A. Nissen, Sander Idema, Piet Van Mieghem, Arjan Hillebrand

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Machine Learning Models for Carbonation Depth Prediction in Reinforced Concrete Structures: A Comparative Study by Rafael Aredes Couto, Igor Augusto Guimarães Campos, Elvys Dias Reis, Daniel Hasan Dalip, Flávia Spitale Jacques Poggiali, Péter Ludvig

“…Moreover, this study reinforces the strategic value of synthetic datasets in developing predictive models when experimental data collection is time-consuming or impractical. …”
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Yield Prediction Models for Rice Varieties Using UAV Multispectral Imagery in the Amazon Lowlands of Peru by Diego Goigochea-Pinchi, Maikol Justino-Pinedo, Sergio S. Vega-Herrera, Martín Sanchez-Ojanasta, Roiser H. Lobato-Galvez, Manuel D. Santillan-Gonzales, Jorge J. Ganoza-Roncal, Zoila L. Ore-Aquino, Alex I. Agurto-Piñarreta

“…The prediction models by variety showed the best performance for Esperanza at 88 DAS (adjusted-R² = 0.94) using EVI as the vegetation index. …”
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Interpretable machine learning models for predicting childhood myopia from school-based screening data by Qi Feng, Xin Wu, Qianwen Liu, Yuanyuan Xiao, Xixing Zhang, Yan Chen

“…Abstract This study assessed the efficacy of various diagnostic indicators and machine learning (ML) models in predicting childhood myopia. A total of 2,365 children aged 5–12 years were included in the study. …”
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PPI-Graphomer: enhanced protein-protein affinity prediction using pretrained and graph transformer models by Jun Xie, Youli Zhang, Ziyang Wang, Xiaocheng Jin, Xiaoli Lu, Shengxiang Ge, Xiaoping Min

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Systematic review and meta-analysis of cardiovascular event risk prediction models in maintenance hemodialysis patients by Yaping Zhou, Yining He, Peiqi Zhu, Ruxue Yan, Ruijie Tang, Lanhui Wang, Weiming He

“…Abstract This research pursues a systematic review and meta-analysis concerning the cardiovascular event risk prediction models for maintenance hemodialysis patients. …”
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Global research trends and hotspots in prognostic prediction models for pancreatic cancer: a bibliometric analysis by Siyuan Ouyang, Jing Zhang, Fuyao Liu, Qi Jiang, Wei Xing, Jie Chen, Jinggang Zhang

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