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In 2020, cancer led to about 10 million deaths worldwide, with breast cancer showing the highest incidence, especially among women. Cancer imposes vast social and economic costs, and its complexity makes it difficult to predict treatment outcomes. Protein aggregates, which form as treatments destroy cancer cells, may serve as indicators of treatment effectiveness. This book presents a smartphone-based system developed to monitor protein aggregate levels via fluorescence intensity, where fluorophore-stained proteins reflect concentration levels. Initial testing with bovine serum albumin and cancer cell extracts were consistent with those from a commercial spectrometer. MATLAB applications were developed for research and clinical use to provide a user-friendly interface for result analysis. By facilitating treatment assessment, this tool may guide timely decisions to modify treatments, potentially enhancing survival rates and reducing costs.