Leveraging artificial intelligence to predict ERG gene fusion status in prostate cancer

Leveraging artificial intelligence to predict ERG gene fusion status in prostate cancer

Background: TMPRSS2-ERG gene rearrangement, the most common E26 transformation specific (ETS) gene fusion within prostate cancer, is known to contribute to the pathogenesis of this disease and carries diagnostic annotations for prostate cancer patients clinically. The ERG rearrangement status in pro...

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Bibliographic Details
Main Authors: Cao, X. (Author), Cheng, J. (Author), Chinnaiyan, A. (Author), Chinnaiyan, A.M (Author), Dadhania, V. (Author), Dhanasekaran, S.M (Author), Gonzalez, D. (Author), Mannan, R. (Author), Mehra, R. (Author), Morgan, T.M (Author), Pantanowitz, L. (Author), Reichert, Z.R (Author), Spratt, D.E (Author), Wang, X. (Author), Yousif, M. (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2022
Subjects:
Adenocarcinoma
Artificial intelligence
Deep learning
ERG
Gene fusion
Prostate cancer
Whole slide imaging
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