Artificial intelligence is the term used to describe the use of computers and technology to simulate intelligent behavior and critical thinking comparable to a human being. In 1956, John McCarthy described the term AI as the science and engineering of making intelligent machines. However, the possibility of machines being able to simulate human behavior and think was raised earlier by Alan Turing who developed the Turing test to differentiate humans from machines and since then the computational power has grown to such extent that new data can be evaluated precisely based on the previously assessed data, in real-time. Today, AI has begun to be incorporated into medicine to improve patient care by speeding up processes and achieving greater accuracy, opening the path to providing better healthcare overall. Radiological images like CT scans, MRI, X-Rays, electronic medical records are evaluated by machine learning models which helps in the process of diagnosing and treatment of the patient. Radiomics is one such advanced technology to diagnose medical images. It extracts a large number of features from medical images via algorithms that help to diagnose disease characteristics. The collected data is in a raw form that can be used to build descriptive and predictive models related to image features. The raw data is mined with other patient data to improve accuracy. The result of these models can provide valuable diagnostics and predictive pieces of information for the tested diseases. The conclusion of radiomics is to reduce medical image diagnosis errors and improve medical facilities. The aim of this study is to present a standard-based evaluation of the disease through radiomics.

CNN Radiomics ML Neural Networks