Letter to the editor: “Not all biases are bad: equitable and inequitable biases in machine learning and radiology”
Abstract Artificial intelligence algorithms are booming in medicine, and the question of biases induced or perpetuated by these tools is a very important topic. There is a greater risk of these biases in radiology, which is now the primary diagnostic tool in modern treatment. Some authors have recen...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2021-06-01
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| Series: | Insights into Imaging |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13244-021-01022-5 |