Novel Human Artificial Intelligence Hybrid Framework Pinpoints Thyroid Nodule Malignancy and Identifies Overlooked Second-Order Ultrasonographic Features

Novel Human Artificial Intelligence Hybrid Framework Pinpoints Thyroid Nodule Malignancy and Identifies Overlooked Second-Order Ultrasonographic Features

We present a Human Artificial Intelligence Hybrid (HAIbrid) integrating framework that reweights Thyroid Imaging Reporting and Data System (TIRADS) features and the malignancy score predicted by a convolutional neural network (CNN) for nodule malignancy stratification and diagnosis. We defined extra...

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Bibliographic Details
Main Authors: Xiaohong Jia, Zehao Ma, Dexing Kong, Yaming Li, Hairong Hu, Ling Guan, Jiping Yan, Ruifang Zhang, Ying Gu, Xia Chen, Liying Shi, Xiaomao Luo, Qiaoying Li, Baoyan Bai, Xinhua Ye, Hong Zhai, Hua Zhang, Yijie Dong, Lei Xu, Jianqiao Zhou, CAAU
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Cancers
Subjects:
thyroid nodule
malignancy risk stratification
feature selection
second-order feature interaction
interpretable deep learning
radiology
Online Access:https://www.mdpi.com/2072-6694/14/18/4440

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https://www.mdpi.com/2072-6694/14/18/4440

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