Predicting recurrence in osteosarcoma via a quantitative histological image classifier derived from tumour nuclear morphological features

Predicting recurrence in osteosarcoma via a quantitative histological image classifier derived from tumour nuclear morphological features

Abstract Recurrence is the key factor affecting the prognosis of osteosarcoma. Currently, there is a lack of clinically useful tools to predict osteosarcoma recurrence. The application of pathological images for artificial intelligence‐assisted accurate prediction of tumour outcomes is increasing. T...

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Bibliographic Details
Main Authors: Zhan Wang, Haoda Lu, Yan Wu, Shihong Ren, Diarra mohamed Diaty, Yanbiao Fu, Yi Zou, Lingling Zhang, Zenan Wang, Fangqian Wang, Shu Li, Xinmi Huo, Weimiao Yu, Jun Xu, Zhaoming Ye
Format: Article
Language:English
Published: Wiley 2023-09-01
Series:CAAI Transactions on Intelligence Technology
Subjects:
diseases
learning (artificial intelligence)
surgery
tumours
Online Access:https://doi.org/10.1049/cit2.12175

Internet

https://doi.org/10.1049/cit2.12175

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