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Title:

Outlier Detection using Self-Organizing Maps for Automated Blood Cell Analysis

Document type:
Konferenzbeitrag
Contribution type:
Textbeitrag / Aufsatz
Author(s):
Röhrl, S., Hein, A., Huang, L., Heim, D., Klenk, C., Lengl, M., Knopp, M., Hafez, N., Hayden, O., Diepold, K.
Abstract:
The quality of datasets plays a crucial role in the successful training and deployment of deep learning models. Especially in the medical field, where system performance may impact the health of patients, clean datasets are a safety requirement for reliable predictions. Therefore, outlier detection is an essential process when building autonomous clinical decision systems. In this work, we assess the suitability of Self-Organizing Maps for outlier detection specifically on a medical dataset cont...     »
Book / Congress title:
2nd Workshop on Interpretable Machine Learning in Healthcare (IMLH 2022)
Year:
2022
Year / month:
2022-12
Language:
en
Publication format:
WWW
Fulltext / DOI:
doi:10.48550/ARXIV.2208.08834
WWW:
https://arxiv.org/abs/2208.08834
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