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Interpretable CNN for ischemic stroke subtype classification with active model adaptation

Version 2 2024-06-06, 08:54
Version 1 2023-10-23, 02:54
journal contribution
posted on 2024-06-06, 08:54 authored by S Zhang, J Wang, L Pei, K Liu, Y Gao, H Fang, R Zhang, L Zhao, S Sun, J Wu, B Song, H Dai, R Li, Y Xu
Background: TOAST subtype classification is important for diagnosis and research of ischemic stroke. Limited by experience of neurologist and time-consuming manual adjudication, it is a big challenge to finish TOAST classification effectively. We propose a novel active deep learning architecture to classify TOAST. Methods: To simulate the diagnosis process of neurologists, we drop the valueless features by XGB algorithm and rank the remaining ones. Utilizing active learning framework, we propose a novel causal CNN, in which it combines with a mixed active selection criterion to optimize the uncertainty of samples adaptively. Meanwhile, KL-focal loss derived from the enhancement of Focal loss by KL regularization is introduced to accelerate the iterative fine-tuning of the model. Results: To evaluate the proposed method, we construct a dataset which consists of totally 2310 patients. In a series of sequential experiments, we verify the effectiveness of each contribution by different evaluation metrics. Experimental results show that the proposed method achieves competitive results on each evaluation metric. In this task, the improvement of AUC is the most obvious, reaching 77.4. Conclusions: We construct a backbone causal CNN to simulate the neurologist process of that could enhance the internal interpretability. The research on clinical data also indicates the potential application value of this model in stroke medicine. Future work we would consider various data types and more comprehensive patient types to achieve fully automated subtype classification.

History

Journal

BMC Medical Informatics and Decision Making

Volume

22

Article number

ARTN 3

Location

England

ISSN

1472-6947

eISSN

1472-6947

Language

English

Publication classification

C1 Refereed article in a scholarly journal

Issue

1

Publisher

BMC