Review Article
Machine Learning: Applications and Advanced Progresses of Radiomics in Endocrine Neoplasms
Table 1
Different clinical applications of radiomic models (features) in PAs.
| References | Case numbers | Radiomic method | Results |
| [20] | 133 | MRI | Radiomic features had promising and practical values in distinguishing pituitary adenoma from Rathke cleft cyst | [21] | 235 | MRI | MRI-based radiomic model could be used to predict immunohistochemical results of pituitary adenoma preoperatively | [22] | 112 | MRI | MRI-based radiomic features had a great potential to differentiate between nonfunctional subtypes and other subtypes pituitary adenomas preoperatively | [24] | 89 | MRI | Radiomics could indirectly predict tumor aggressiveness by predicting high proliferative index Ki-67 in pituitary macroadenomas | [25] | 194 | MRI | MRI-based radiomic method was proved to be an effective method for predicting the cavernous sinus invasion preoperatively | [28] | 163 | MRI | Radiomics models may help neurosurgeons predict the treatment response preoperatively and make personalized treatment strategies | [26] | 400 | MRI | The result indicated that early postoperative outcomes of PAs could be assessed by a radiomic approach |
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