Key concepts, common pitfalls, and best practices in artificial intelligence and machine learning: focus on radiomics-Reference-Cited by-同舟云学术

Key concepts, common pitfalls, and best practices in artificial intelligence and machine learning: focus on radiomics

Published:2022-10-11 Issue:5 Volume:28 Page:450-462
ISSN:
Container-title:Diagnostic and Interventional Radiology
language:
Short-container-title:Diagn Interv Radiol

Author:

Kocak Burak,

Publisher

Galenos Yayinevi

Subject

Economics and Econometrics,Finance,Accounting,Finance,Strategy and Management,General Social Sciences,General Engineering,Safety, Risk, Reliability and Quality,Health Informatics,Surgery,Control and Systems Engineering,General Computer Science,Control and Systems Engineering,Electrical and Electronic Engineering,General Computer Science,Geotechnical Engineering and Engineering Geology,Literature and Literary Theory,Linguistics and Language,Visual Arts and Performing Arts,Language and Linguistics,Cultural Studies,Organic Chemistry,Plant Science

Cited by 19 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Towards autonomous learning and optimisation in textile production: data-driven simulation approach for optimiser validation;Journal of Intelligent Manufacturing;2024-05-24

2. Applying oversampling before cross-validation will lead to high bias in radiomics;Scientific Reports;2024-05-21

3. Application of Artificial Intelligence Methods on Osteoporosis Classification with Radiographs—A Systematic Review;Bioengineering;2024-05-12

4. Understanding and Mitigating Bias in Imaging Artificial Intelligence;RadioGraphics;2024-05-01

5. Advancing Fairness in Cardiac Care: Strategies for Mitigating Bias in Artificial Intelligence Models Within Cardiology;Canadian Journal of Cardiology;2024-05