| Title | Semi-Supervised, Attention-Based Deep Learning for Predicting TMPRSS2:ERG Fusion Status in Prostate Cancer Using Whole Slide Images. |
| Publication Type | Journal Article |
| Year of Publication | 2024 |
| Authors | Omar M, Xu Z, Rand SB, Alexanderani MK, Salles DC, Valencia I, Schaeffer EM, Robinson BD, Lotan TL, Loda M, Marchionni L |
| Journal | Mol Cancer Res |
| Volume | 22 |
| Issue | 4 |
| Pagination | 347-359 |
| Date Published | 2024 Apr 02 |
| ISSN | 1557-3125 |
| Keywords | Deep Learning, Humans, Male, Oncogene Proteins, Fusion, Prostatectomy, Prostatic Neoplasms, Serine Endopeptidases, Transcriptional Regulator ERG |
| 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. |
| DOI | 10.1158/1541-7786.MCR-23-0639 |
| Alternate Journal | Mol Cancer Res |
| PubMed ID | 38284821 |
| PubMed Central ID | PMC10985477 |
| Grant List | R01 CA200859 / CA / NCI NIH HHS / United States T32 CA260293 / CA / NCI NIH HHS / United States U54 CA273956 / CA / NCI NIH HHS / United States |
Related Faculty:
Brian Robinson, M.D. Massimo Loda, M.D. Mohamed Omar, MB, BCh Luigi Marchionni, M.D., Ph.D.