Personalized Medicine

Personalized medicine aims to tailor medical treatments to individual patients based on their unique characteristics, primarily using genomic and other omics data, alongside clinical information and lifestyle factors. Current research heavily utilizes machine learning, including neural networks (e.g., LSTMs, CNNs, graph neural networks), and advanced algorithms like reinforcement learning, to analyze this complex data and predict optimal treatment strategies, often incorporating techniques for handling missing data and addressing biases. This approach holds significant promise for improving treatment efficacy, reducing adverse effects, and ultimately enhancing patient outcomes across various diseases, particularly cancer and chronic conditions like diabetes.