ABSTRACT
Any injury to the brain may result in an abnormal growth of the brain tissue that is responsible for performing cognitive activities. This will ultimately lead to the development of a tumor inside the brain. This will be a great risk to an individual's life if not diagnosed at an early stage, as these abnormal brain cells grow quickly and may spread to other parts of the body, potentially causing skin, lung, and breast cancer as well. Although most medical professionals rely on magnetic resonance imaging (MRI), computed tomography (CT) scans, and other techniques for diagnosing a brain tumor, it is quite possible the tumor will remain undetected in its early stages due to its extremely small size. Therefore, a smart healthcare system is in demand in the medical field to provide analysis of medical images and early detection of abnormalities and disease, resulting in better outcomes and a longer life expectancy for patients. Using real-time monitoring, this system would generate large quantities of data for electronic healthcare records and then deep learning would take over to offer great tools for analysis, as well as extracting meaningful information from the raw data. If the existing issues of interpretability, privacy of data, insufficient data, etc., could be solved using deep learning, this would enable experts to consider such automated systems as a trustworthy second opinion with efficient and accurate outcomes, as compared with the existing techniques. This chapter presents a discussion of these game-changing applications that are available for use by professionals in the healthcare sector.
