AI-Driven COVID-19 Patient Screening With Design Thinking Approach- C3IA Tool

Abstract

In this chapter, the authors discuss a brief literature review on AI-driven COVID-19 patient screening technologies along with their pros and cons. Next, they discuss the need of human-centric design thinking in AI-driven solutions. Next, in this study, a novel C3IA (CNN-based COVID-19 chest image analysis) tool for automatic COVID-19 detection with multi-class classification (COVID/normal/pneumonia) using raw chest x-ray images is proposed. The authors implemented a two-stream CNN architecture with two pre-trained VGG-16 models, which incorporates both segmented and un-segmented image features. The trained model is tested on more than 500 Indian patient x-ray image datasets and confirmed accuracy of 99% in detecting COVID signatures. Further, in this work, the authors discuss how the design thinking approach is followed in various stages while developing the product to provide a user-friendly efficient real-time COVID-19 chest x-ray image analysis for the common citizen.

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