Medical Image Classification for Early Disease Detection

Medical imaging is among the frontline modes of investigations for early disease diagnosis, hence their timely interventions. A project such as this could be done by leveraging machine learning to perform a classification of medical images into early diagnosis. In this project, we will gather a dataset comprising a wide variety of medical images ranging from X-ray, MRI, and CT scans to histopathology slides. Normalization, standardization, and augmentation techniques will be done to preprocess the dataset for further quality and improvement in model robustness. This might improve diagnostic accuracy and simplify the diagnosis process for different types of diseases.