Abstract
Our study illuminates the potential of deep learning in effectively inferring key prostate cancer genetic alterations from the tissue morphology depicted in routinely available histology slides, offering a cost-effective method that could revolutionize diagnostic strategies in oncology.
©2024 The Authors; Published by the American Association for Cancer Research.
Publication types
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Research Support, N.I.H., Extramural
MeSH terms
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Deep Learning*
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Humans
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Male
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Oncogene Proteins, Fusion / genetics
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Prostatectomy
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Prostatic Neoplasms* / pathology
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Serine Endopeptidases / genetics
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Transcriptional Regulator ERG
Substances
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Oncogene Proteins, Fusion
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ERG protein, human
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Transcriptional Regulator ERG
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TMPRSS2 protein, human
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Serine Endopeptidases