Deep Reinforcement Learning Framework for Thoracic Diseases Classification via Prior Knowledge Guidance

by   Weizhi Nie, et al.

The chest X-ray is often utilized for diagnosing common thoracic diseases. In recent years, many approaches have been proposed to handle the problem of automatic diagnosis based on chest X-rays. However, the scarcity of labeled data for related diseases still poses a huge challenge to an accurate diagnosis. In this paper, we focus on the thorax disease diagnostic problem and propose a novel deep reinforcement learning framework, which introduces prior knowledge to direct the learning of diagnostic agents and the model parameters can also be continuously updated as the data increases, like a person's learning process. Especially, 1) prior knowledge can be learned from the pre-trained model based on old data or other domains' similar data, which can effectively reduce the dependence on target domain data, and 2) the framework of reinforcement learning can make the diagnostic agent as exploratory as a human being and improve the accuracy of diagnosis through continuous exploration. The method can also effectively solve the model learning problem in the case of few-shot data and improve the generalization ability of the model. Finally, our approach's performance was demonstrated using the well-known NIH ChestX-ray 14 and CheXpert datasets, and we achieved competitive results. The source code can be found here: <>.


page 1

page 5

page 11


Cardiomegaly Detection using Deep Convolutional Neural Network with U-Net

Cardiomegaly is indeed a medical disease in which the heart is enlarged....

Self-supervised deep convolutional neural network for chest X-ray classification

Chest radiography is a relatively cheap, widely available medical proced...

KoGuN: Accelerating Deep Reinforcement Learning via Integrating Human Suboptimal Knowledge

Reinforcement learning agents usually learn from scratch, which requires...

Efficient Symptom Inquiring and Diagnosis via Adaptive Alignment of Reinforcement Learning and Classification

The medical automatic diagnosis system aims to imitate human doctors in ...

Instrumental Variable Learning for Chest X-ray Classification

The chest X-ray (CXR) is commonly employed to diagnose thoracic illnesse...

Online Learning and Planning in Partially Observable Domains without Prior Knowledge

How an agent can act optimally in stochastic, partially observable domai...

Dynamic transformation of prior knowledge into Bayesian models for data streams

We consider how to effectively use prior knowledge when learning a Bayes...

Please sign up or login with your details

Forgot password? Click here to reset