UC Merced Undergraduate Research Journal

The rapid growth of cancer is the second-leading cause of death in the U.S., and lung cancer has the highest mortality rate. This, in turn, creates a high demand for new technology to effectively treat this disease. This synthesis project delves into the capabilities of AI technologies that are specialized in diagnosing lung cancer at an early stage and their effectiveness in creating personalized treatment and risk prevention. By understanding more about the Explainable Artificial Intelligence (XAI) tool along with the Triplet Network method, the study reveals that it has a high accuracy rate (86.39%) on early diagnosis of lung cancer and can examine a patient’s genome for cancer risk. The application of AI technology for the diagnosis of complex diseases like cancer is essential for maximizing patients’ safety and recovery, along with the reassurance that medical professionals need. As AI technology continually improves over time, it may soon perform more complex tasks than simply scanning and analyzing data.