Use of artificial neural networks to predict anterior communicating artery aneurysm rupture: possible methodological considerations
Use of algorithms to generate synthetic cases might result in a misrepresentation of the entire population.
Training an artificial neural network with a mix of real and synthetic data might lead to non-realistic prediction precision.
We would like to acknowledge professor Ronald Bartels for his constructive contributions to the presented work.
The authors state that this work has not received any funding.
Compliance with ethical standards
The scientific guarantor of this publication is Ronald Bartels (head of the neurosurgery department).
Conflict of interest
The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.
Statistics and biometry
No complex statistical methods were necessary for this paper.
Written informed consent was not required for this study because data collection from human subjects was not needed.
Institutional Review Board approval was not required because synthetic data was generated for this study.
• Performed at one institution
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