A review of the machine learning datasets in mammography, their adherence to the FAIR principles and the outlook for the future
Abstract The increasing rates of breast cancer, particularly in emerging economies, have led to interest in scalable deep learning-based solutions that improve the accuracy and cost-effectiveness of mammographic screening. However, such tools require large volumes of high-quality training data, whic...
Main Authors: | Joe Logan, Paul J. Kennedy, Daniel Catchpoole |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2023-09-01
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Series: | Scientific Data |
Online Access: | https://doi.org/10.1038/s41597-023-02430-6 |
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