MATLAB's robust computational capabilities allow researchers to handle large datasets, perform statistical analyses, and create sophisticated models. Here are some specific applications:
Image Processing: MATLAB is extensively used in medical image processing to analyze images from MRI, CT scans, and histopathology slides. This aids in the detection and classification of tumors. Data Analysis: Researchers can use MATLAB to analyze genomic, proteomic, and metabolomic data, leading to the identification of potential biomarkers and therapeutic targets. Machine Learning: MATLAB supports machine learning and deep learning algorithms that can be applied to predict cancer outcomes, classify cancer types, and personalize treatment plans. Simulation and Modeling: MATLAB is used to model cancer cell behavior, simulate drug interactions, and understand the dynamics of tumor growth.
