"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 early cancer detection. In one study, researchers used microbiome-based biomarkers (see Microbiome) with ML models to improve early detection of pancreatic cancer. Using information about the microbiome from blood samples, researchers developed ML models capable of distinguishing patients with pancreatic cancer from healthy individuals with over 95 percent accuracy (1038)Lee D, et al. (2025) Sci Rep, 15: 10995.. This represents a major advance for a cancer that is extremely difficult to detect early and has one of the highest mortality rates due to late-stage diagnosis. In another study, researchers developed an ML model to analyze samples from noninvasive blood-based liquid biopsies (see Liquid Biopsy in Cancer Care) that detected gliomas across all grades with high sensitivity (1039)Mathios D, et al. (2025) Cancer Discov..\n\nTogether, these examples demonstrate how AI-powered diagnostic tools are advancing earlier, less invasive detection of some of the deadliest cancers, particularly those that often go unnoticed until symptoms appear at more advanced stages. In addition to helping with early detection of difficult-to-detect cancers, AI is also accelerating improved detection of cancers for which effective screening methods already exist, such as helping read mammograms to detect breast cancer faster, more accurately, and efficiently (see Technological Innovations Advance Cancer Screening for Early Detection)."