Previous projects

This paper investigates the possibility of using feature extraction with a convolutional neural network for classification of power Doppler ultrasound images of RA.

An accuracy of 75.0 % was achieved for 4-class
classification. An accuracy of 86.9 %, a sensitivity of 87.5 %, and a specificity of 86.4 % was achieved for binary classification.
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To achieve insight into possible barriers within a group of patients with rheumatoid arthritis, qualitative and quantitative studies have been performed in this research.

32 patients with rheumatoid arthritis are interviewed to investigate the interaction between patients and RoPCA. The interviews found that 90% of  patients are willing to use the automated ultrasound scanning robot.
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