ROLE OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN CANCER DIAGNOSIS

Abstract

AI tool machine learning algorithms and deep neural networks, these tools can analyze medical images such as CT scans, MRI, and PET scans to identify patterns and features that may be indicative of cancer. They can also assist in the segmentation and classification of tumours, helping to provide more accurate diagnoses and personalized treatment plans. Radiomics is one area of AI research that has shown potential in cancer diagnosis. Radiomics involves the extraction of large amounts of quantitative data from medical images, which can be used to build predictive models for diagnosis and treatment planning. Texture analysis, which involves the analysis of the spatial arrangement of pixel intensities in an image, is another important technique used in cancer diagnosis with AI tools. In addition to medical imaging, AI tools are also being developed to analyze other types of data, such as genomic data, to better understand the genetic factors that contribute to cancer development and progression. This has the potential to lead to more personalized treatment plans based on a patient's unique genetic profile.