Radiology images in machine learning: Diagnosing and combatting COVID-19

The COVID-19 pandemic has created an unprecedented demand for effective and timely diagnostic solutions to combat its spread. Radiology imaging has emerged as a crucial tool in diagnosing and monitoring COVID-19 due to its noninvasive nature and ability to reveal characteristic features of the disease. Machine learning techniques have played a pivotal role in analyzing radiology images, enabling accurate and rapid COVID-19 detection. This chapter provides a comprehensive overview of radiology imaging modalities, including X-ray and CT scans, commonly employed for COVID-19 diagnosis. It explores key features and characteristics visible in radiology images that aid in identifying COVID-19 infections. Nevertheless, radiology imaging faces challenges, such as false negatives and potential overutilization. Machine learning techniques are extensively discussed, encompassing preprocessing methods to ensure data quality, feature extraction and selection techniques for identifying relevant patterns, and classification algorithms, including deep learning architectures, for precise COVID-19 detection. The importance of interpretability in medical imaging for COVID-19 diagnosis is emphasized, along with various techniques for explaining and interpreting machine-learning models. Despite challenges in achieving full interpretability, these techniques enhance trust and confidence in the diagnostic process. Recent advancements and innovations in COVID-19 detection research are explored, with a focus on multimodal imaging integration for improved accuracy and transfer learning and domain adaptation techniques. These advancements show promise in enhancing diagnostic efficiency and performance. However, deploying machine learning for COVID-19 diagnosis raises ethical considerations and requires addressing dataset biases and disparities. Future research directions are proposed to further improve model interpretability, enhance dataset representation, and advance machine learning for COVID-19 diagnosis. In conclusion, radiology imaging combined with machine learning presents a powerful approach in diagnosing and combatting COVID-19. By addressing challenges and embracing innovations responsibly, this synergistic approach holds great potential to significantly impact the global fight against COVID-19 and improve patient outcomes.