
פרופ' אסף זריצקי
Visual interpretability of bioimaging deep learning models
The success of deep learning in analyzing bioimages comes at the expense of biologically meaningful interpretations. We review the state of the art of explainable artificial intelligence (XAI) in bioimaging and discuss its potential in hypothesis generation and data-driven discovery.
| שפת פרסום | אנגלית |
| דפים | 1394-1397 |
| כתב עת | Nature Methods |
| כרך | 21 |
| נושא מספר | 8 |
| סטטוס פרסום | פורסם - 01.08.2024 |
ASJC Scopus subject areas
Biotechnology
Biochemistry
Molecular Biology
Cell Biology