Artificial Intelligence in Medical Imaging by Machine Learning and Deep Learning

2. Artificial Intelligence (Ai) In Medical Imaging Domains

AI is being hailed as the most transformative technology in health care in the twenty-first century. Artificial intelligence (AI) applications, especially in medical imaging, are among the most exciting new directions in health innovation. This chapter defines key topics like “machine learning” and “deep learning” and examines how AI is being used in radiology. In fact, artificial intelligence has a wide range of applications, including picture collecting and processing, help with reporting, monitoring, data mining, storing, and numerous additional tasks. AI is predicted to have a significant influence on the radiologist's everyday life as a result of its broad variety of applications (Lakhani, 1018). There is universal agreement that AI will alter the healthcare business, notably diagnostics in the field of medical imaging. By merging radiomics with AI, more advancements in health prevention, accuracy, and management are on the horizon. Furthermore, advancements in AI-driven health prevention, accuracy, and management are on the horizon as a result of merging radiomics from medical pictures with other data formats such as genomes, proteomics, and demography. Within medical imaging, possibility of introduction of AI technologies at the local level is being explored to minimize labor demanding and repetitive processes such as medical picture interpretation. The potential to develop AIs in fields like natural language processing (NLP) is expanding along with our information systems' ability to gather large amounts of data from Australian, in 2019.

Figure 1.

Domains of deep learning, machine learning, and artificial intelligence