Big Data Analytics and Radiomics to Discover Diagnostics and Therapeutics for Gastric Cancer

Cancer is the cause of early death and it is unique. A cancer diagnosis is complicated, and treatment outcomes vary from patient to patient. Improving cancer diagnosis may help in early diagnosis and reduces early deaths. The most common method for the diagnosis of gastrointestinal cancer is gastroscopic imaging. The availability of white light, non-magnifying images, and manual pathological examination are the major drawbacks of the system. Imaging methods like X-Ray, Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Nuclear Medicine (NM) Positron Emission Tomography (PET), and Ultrasound (US) had revolutionized the diagnosis of gastrointestinal cancer. The disadvantage with these radiological images is that they contain more information and content, which is not visible to the clinician’s eye. Radiomics is a process of conversion of digital medical images into mineable high-dimensional data. In this chapter, the use of big data in radiomics as a tool for gastrointestinal cancer diagnosis and prognosis is discussed. This provides information and helps in the early detection of gastrointestinal cancer.