Submitted by ptc4001 on July 20, 2021 - 1:04pm
| Title | Towards artificial intelligence-driven pathology assessment for hematological malignancies. |
| Publication Type | Journal Article |
| Year of Publication | 2021 |
| Authors | Elemento O |
| Journal | Blood Cancer Discov |
| Volume | 2 |
| Issue | 3 |
| Pagination | 195-197 |
| Date Published | 2021 May |
| ISSN | 2643-3249 |
| Abstract | In this issue of Blood Cancer Discovery, Brück applied unsupervised and supervised machine learning to bone marrow histopathology images from Myelodysplastic Syndrome (MDS) patients. Their study provides new insights into the pathobiology of MDS and paves the way for increased use of artificial intelligence for the assessment and diagnosis of hematological malignancies. |
| DOI | 10.1158/2643-3230.bcd-21-0048 |
| Alternate Journal | Blood Cancer Discov |
| PubMed ID | 34027414 |
| PubMed Central ID | PMC8133372 |
| Grant List | R01 CA194547 / CA / NCI NIH HHS / United States UG3 CA244697 / CA / NCI NIH HHS / United States UL1 TR002384 / TR / NCATS NIH HHS / United States |