Deep Learning Based on Magnetic Resonance Imaging for Preoperative Prediction of Pituitary Neuroendocrine Tumors Subtypes.
Molecular subtyping of pituitary neuroendocrine tumors (PitNETs [pituitary adenoma]) guides treatment but requires postoperative pathology. This study aimed to develop a deep learning model for preoperative noninvasive prediction of PitNET subtypes using magnetic resonance imaging (MRI).
Molecular subtyping of pituitary neuroendocrine tumors (PitNETs [pituitary adenoma]) guides treatment but requires postoperative pathology. This study aimed to develop a deep learning model for preoperative noninvasive prediction of PitNET subtypes using magnetic resonance imaging (MRI).
What the study was
- Study design
- Cohort/Observational Study
- Category
- Treatment Innovation
- Maturity
- Validated
- Journal
- Acad Radiol
Why it surfaced
Matched watchlist topic 'AI/ML in clinical diagnostics and imaging'. Study design: Cohort/Observational Study. Score: 8/10 (N:2, R:3, D:1, P:2).
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