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The availability of disease‐specific genomic data is critical for developing new computational methods that predict the pathogenicity of human variants and advance the field of precision medicine. However, the lack of gold standards to properly train and benchmark such methods is one of the greatest challenges in the field. In response to this challenge, the scientific community is invited to participate...
We propose a multi-stage detection system for microcalcification. A connectionist online feature selection technique is used to identify a set of good features from a set of 87 features computed at a few randomly selected positive (calcified) and negative (normal) pixels. A neural network is then trained with the selected features. The network output is cleaned using connected component analysis and...
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