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However, the diagnostic accuracy is potentially influenced by training databases.
Notable effects of training databases differ among prostate, breast, and other cancers.
Training databases are essential for a neural network system to diagnose bone metastases.
Methods of these types require training databases of scans to mimic interpretation by experts.
The demographics of the patients from the different training databases are shown in Table 1.
In virtue of a concept of "Digital Damage Fingerprints" (DDF), a hierarchical approach for the development of training databases was proposed for ANN-based damage identification.
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Table 3 reports the training database.
Suffix database was created using the same training database.
One day the Aetna training database might crash.
We collected 100,000 coupled patches as the external training database.
To characterize the range of body shape variation, the training database was analyzed statistically.
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