Personalized Chemotherapy Selection for Lung Cancer Patients Using Machine Learning and Computed Tomography

The treatment of lung cancer remains a significant challenge in modern medicine, with no universally optimal treatment regimen established to date. In this study, we focused on investigating the efficacy and suitability of Carboplatin as a chemotherapy drug for lung cancer treatment. Utilizing machine learning algorithms and analyzing computed tomography (CT) data, we aimed to determine if Carboplatin or Cisplatin emerges as the best therapeutic option. Our methodology involved collecting and preprocessing clinical data, extracting deep features from CT images, developing a machine learning algorithm for image classification, and evaluating the performance of our approach. The results of our study provide valuable insights into the effectiveness of Carboplatin as a chemotherapy drug for lung cancer, aiding physicians in making informed treatment decisions based on individual patient characteristics. This research contributes to the advancement of personalized medicine and highlights the potential of machine learning and CT imaging in optimizing lung cancer treatment outcomes.