Performance of MRI-based deep learning models in differentiation of triple negative breast cancer from other breast cancer subtypes: A systematic review and meta-analysis.
BACKGROUND AND AIM: Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer with limited targeted therapies. Deep learning (DL) applied to magnetic resonance imaging (MRI) offers a promising noninvasive alternative to biopsy.
BACKGROUND AND AIM: Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer with limited targeted therapies. Deep learning (DL) applied to magnetic resonance imaging (MRI) offers a promising noninvasive alternative to biopsy.
What the study was
- Study design
- Meta-Analysis
- Category
- Diagnostics
- Maturity
- Potentially Practice-Changing
- Journal
- European journal of radiology open
Why it surfaced
HIGH priority (score 8/10); study design: Meta-Analysis; topic: AI/ML in clinical diagnostics and imaging; flag: PROMISING_PRELIMINARY
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