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Titlebook: Explainable Machine Learning in Medicine; Karol Przystalski,Rohit M. Thanki Book 2024 The Editor(s) (if applicable) and The Author(s), und

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樓主: GOLF
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發(fā)表于 2025-3-23 11:14:08 | 只看該作者
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發(fā)表于 2025-3-23 17:42:07 | 只看該作者
Book 2024sis desired. Because a variety of data can be used in the medical field, the book explains how to deal with challenges connected with each type. A number of scenarios are introduced that can happen in real-time environments, with each pared with a type of machine learning that can be used to solve it..
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發(fā)表于 2025-3-23 20:55:22 | 只看該作者
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發(fā)表于 2025-3-24 02:02:09 | 只看該作者
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發(fā)表于 2025-3-24 15:23:13 | 只看該作者
Handbook of Spectral Lines in Diamondsimple example of this type of data. We have the weight, age, and height values divided by the person to which they are assigned. Such data might be too simple to be used with a deep neural network or even most shallow methods, but we can use methods such as linear regression to see the correlation
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發(fā)表于 2025-3-24 20:02:21 | 只看該作者
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發(fā)表于 2025-3-25 02:43:33 | 只看該作者
https://doi.org/10.1007/978-981-16-3679-0he medical diagnostics on a daily basis. The most typical are X-ray and ultrasound scans. Some General Practitioners have a dermatoscope to take pictures of the skin. Similarly, thermography can be used to take kind of heatmap images of our body. If the diagnosis of a disease is more complex, magnet
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