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Support vector machines

Optimal selection of resampling methods for imbalanced data with high complexity

Annie Kim, Inkyung Jung

CT radiomics for differentiating fat poor angiomyolipoma from clear cell renal cell carcinoma: Systematic review and meta-analysis

Fatemeh Dehghani Firouzabadi, Nikhil Gopal, [ ... ], Ashkan A. Malayeri

A machine learning approach to model the impact of line edge roughness on gate-all-around nanowire FETs while reducing the carbon footprint

Antonio García-Loureiro, Natalia Seoane, [ ... ], Juan C. Pichel

Machine learning‐based identification and related features of depression in patients with diabetes mellitus based on the Korea National Health and Nutrition Examination Survey: A cross-sectional study

Ji-Yoon Lee, Doyeon Won, Kiheon Lee

Anxiety classification in virtual reality using biosensors: A mini scoping review

Deniz Mevlevioğlu, Sabin Tabirca, David Murphy

Football players’ strength training method using image processing based on machine learning

Xiaoxiang Cao, Xiaodong Zhao, [ ... ], Fateh Zereg

Analysis and classification of 1H-NMR spectra by multifractal analysis

Jongphil Kim, Hin Kyeol Woo, Dixon Vimalajeewa, Brani Vidakovic

Using machine learning-based systems to help predict disengagement from the legal proceedings by women victims of intimate partner violence in Spain

Elena Escobar-Linero, María García-Jiménez, [ ... ], Manuel Domínguez-Morales

The effect of seasonality in predicting the level of crime. A spatial perspective

Rosario Delgado, Héctor Sánchez-Delgado

Improvement of predictive accuracies of functional outcomes after subacute stroke inpatient rehabilitation by machine learning models

Yuta Miyazaki, Michiyuki Kawakami, [ ... ], Tetsuya Tsuji

Semi-supervised nuclei segmentation based on multi-edge features fusion attention network

Huachang Li, Jing Zhong, [ ... ], Peng Shi

Developing forecasting model for future pandemic applications based on COVID-19 data 2020–2022

Wan Imanul Aisyah Wan Mohamad Nawi, Abdul Aziz K. Abdul Hamid, [ ... ], Mohd Tajuddin Abdullah

Predicting nutritional status for women of childbearing age from their economic, health, and demographic features: A supervised machine learning approach

Md. Mohsan Khudri, Kang Keun Rhee, Mohammad Shabbir Hasan, Karar Zunaid Ahsan

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