Chapter

Improving Detection and Diagnosis

From Future of Cancer Science | AACR Cancer Progress Report 2025 by Sambif

Concepts

1. AI Diagnosis

   "AI-driven tools have the potential to offer faster, more accurate, and less invasive methods to detect and diagnose cancer. As one example, using over 163,000 low-dose computed tomography (CT) scans

2. Biomarkers

   "Recent advances in ML technologies are harnessing noninvasive biomarkers—measurable molecular markers found in body fluids that can signal the presence of disease or response to treatment—to improve

3. Tumor Classification

   "Recent studies show that AI can improve how patients are classified based on their tumor’s characteristics. For instance, researchers developed a DL model that accurately predicts EGFR and KRAS mutat

4. Cancer Spread

   "AI applications are also showing promise in predicting when and where in the body cancer will spread and whether it will come back. For example, a recent study showed that ML models predicted aggress