Cancer is one of the most painful and deadly diseases one can get in modern times. With early cancer detection being a significant factor which determines said dread.

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With technology and science advancing on a daily basis, an easier and less painful method for cancer detection is no longer a dream.

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We aim to design an algorithm that utilizes machine learning and artificial intelligence to detect tissue heterogeneity without the need to carry out a biopsy. Using radiomics biomarkers to extract high quantitative features that  will determine if the patient has tissue heterogeneity, such as cancer. This project is of interest to many different hospitals around the world as it excludes the need for biopsies as they can be uncomfortable, and very expensive, and physically taxing on the patients.

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This project will revolutionize the way doctors detect cancer, making it a more efficient and accurate process.