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Boosting algorithms

Expected goals in football: Improving model performance and demonstrating value

James Mead, Anthony O’Hare, Paul McMenemy

published 05 Apr 2023

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Detecting CTP truncation artifacts in acute stroke imaging from the arterial input and the vascular output functions

Ezequiel de la Rosa, Diana M. Sima, Jan S. Kirschke, Bjoern Menze, David Robben

published 30 Mar 2023

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Machine learning with textural analysis of longitudinal multiparametric MRI and molecular subtypes accurately predicts pathologic complete response in patients with invasive breast cancer

Aaquib Syed, Richard Adam, Thomas Ren, Jinyu Lu, Takouhie Maldjian, Tim Q. Duong

published 17 Jan 2023

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Implementing machine learning methods with complex survey data: Lessons learned on the impacts of accounting sampling weights in gradient boosting

Nathaniel MacNell, Lydia Feinstein, Jesse Wilkerson, Pӓivi M. Salo, Samantha A. Molsberry, Michael B. Fessler, Peter S. Thorne, Alison A. Motsinger-Reif, Darryl C. Zeldin

published 13 Jan 2023

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Artificial intelligence automates the characterization of reversibly actuating planar-flow-casted NiTi shape memory alloy foil

Ritaban Dutta, Ling Chen, David Renshaw, Daniel Liang

published 19 Oct 2022

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An empirical evaluation of sampling methods for the classification of imbalanced data

Misuk Kim, Kyu-Baek Hwang

published 28 Jul 2022

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Machine learning techniques for forecasting agricultural prices: A case of brinjal in Odisha, India

Ranjit Kumar Paul, Md. Yeasin, Pramod Kumar, Prabhakar Kumar, M. Balasubramanian, H. S. Roy, A. K. Paul, Ajit Gupta

published 06 Jul 2022

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Predicting the number of days in court cases using artificial intelligence

Raphael Souza de Oliveira, Amilton Sales Reis Jr., Erick Giovani Sperandio Nascimento

published 26 May 2022

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E-CatBoost: An efficient machine learning framework for predicting ICU mortality using the eICU Collaborative Research Database

Nima Safaei, Babak Safaei, Seyedhouman Seyedekrami, Mojtaba Talafidaryani, Arezoo Masoud, Shaodong Wang, Qing Li, Mahdi Moqri

published 05 May 2022

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Using machine learning to understand age and gender classification based on infant temperament

Maria A. Gartstein, D. Erich Seamon, Jennifer A. Mattera, Michelle Bosquet Enlow, Rosalind J. Wright, Koraly Perez-Edgar, Kristin A. Buss, Vanessa LoBue, Martha Ann Bell, Sherryl H. Goodman, Susan Spieker, David J. Bridgett, Amy L. Salisbury, Megan R. Gunnar, Shanna B. Mliner, Maria Muzik, Cynthia A. Stifter, Elizabeth M. Planalp, Samuel A. Mehr, Elizabeth S. Spelke, Angela F. Lukowski, Ashley M. Groh, Diane M. Lickenbrock, Rebecca Santelli, Tina Du Rocher Schudlich, Stephanie Anzman-Frasca, Catherine Thrasher, Anjolii Diaz, Carolyn Dayton, Kameron J. Moding, Evan M. Jordan

published 13 Apr 2022

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3-Dimensional convolutional neural networks for predicting StarCraft Ⅱ results and extracting key game situations

Insung Baek, Seoung Bum Kim

published 03 Mar 2022

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Actionable absolute risk prediction of atherosclerotic cardiovascular disease based on the UK Biobank

Ajay Kesar, Adel Baluch, Omer Barber, Henry Hoffmann, Milan Jovanovic, Daniel Renz, Bernard Leon Stopak, Paul Wicks, Stephen Gilbert

published 11 Feb 2022

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Predicting risk for trauma patients using static and dynamic information from the MIMIC III database

Evan J. Tsiklidis, Talid Sinno, Scott L. Diamond

published 19 Jan 2022

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