Despite its potential, implementing machine learning in cancer treatment and research comes with challenges. Data quality and availability are major hurdles, as the accuracy of machine learning models depends on the data they are trained on. Additionally, integrating machine learning solutions into existing medical workflows can be complex and requires collaboration between technologists and healthcare professionals. AWS offers comprehensive support and resources to help overcome these challenges, but a multidisciplinary approach is essential for success.
