Lung cancer kills more people than any other cancer because it is so often caught too late. According to the World Health Organization, it accounts for nearly 1 in 5 cancer deaths worldwide. The tragedy lies not only in its aggressiveness, but in the fact that current screening methods such as chest X-rays or CT scans fail to consistently detect tumors at their earliest, most curable stages. By the time symptoms appear, the disease has often advanced too far for treatment to be effective. For decades, scientists have sought a breakthrough in early detection that could change survival rates dramatically.
But a sign of that future may already be here and it’s being developed not in a corporate lab or university hospital, but by a high school researcher. Aarnav Bhat, a YRI Fellow, has demonstrated what could be a game-changing step forward.
In his project, “AI-Powered DNA Methylation Biomarkers for Early Lung Cancer Detection,” Aarnav tackled one of medicine’s hardest problems by combining artificial intelligence with epigenetics, the study of chemical modifications to DNA that regulate gene expression. Unlike mutations, these changes do not alter the DNA sequence itself but can signal the presence of diseases such as cancer.
Using over 7,000 patient samples, Aarnav trained a machine learning model to analyze five critical DNA methylation biomarkers EGFR, PD-L1, SHOX2, RASSF1A, and PTGER4. These biomarkers are well-documented in cancer research, each associated with tumor growth or immune system evasion. By training his AI to detect patterns across this data, Aarnav created a diagnostic system that achieved 98.2% sensitivity and an AUC (Area Under Curve) of 0.983. These performance metrics surpass many existing clinical tools, which often hover around lower accuracy levels and are inconsistent across patient populations.
What makes this achievement especially powerful is its potential real-world impact. The system is non-invasive, cost-effective, and adaptable across cancer stages and diverse populations. That means it could realistically be deployed in hospitals worldwide, including in low-resource settings where access to expensive imaging technology is limited. With early detection being the difference between life and death for lung cancer patients, the implications of Aarnav’s work are enormous.
“This is not just about accuracy numbers,” said one YRI mentor who guided Aarnav. “It’s about showing that early detection doesn’t have to be expensive, invasive, or limited to elite clinics. What Aarnav has done demonstrates that the power of AI can democratize access to life-saving tools.”
This is exactly what the YRI Fellowship was built for: to empower ambitious high school students to work at the cutting edge of real science. While most students are memorizing textbooks or performing simple lab experiments, YRI Fellows like Aarnav are publishing research, presenting at conferences, and developing innovations that could transform healthcare.
Backed by PhD-level mentorship and a global community of young researchers, YRI provides Fellows with the structure, accountability, and expertise they need to compete at the level of graduate researchers. The program’s approach flips the traditional model of science education on its head: instead of delaying real research until graduate school, YRI believes in treating high schoolers as scientists today. The results speak for themselves in the groundbreaking projects that emerge year after year.
Aarnav’s project is more than an experiment it’s a milestone in precision oncology. By revealing how AI can detect hidden epigenetic patterns, his work opens the door for multi-modal cancer diagnostics that could one day integrate genomics, metabolomics, imaging, and beyond. This convergence of biology and artificial intelligence is at the frontier of medicine, where treatments are increasingly personalized to the unique molecular profile of each patient. With this research, Aarnav is not only making headlines he’s paving the road to the next generation of personalized medicine.
The YRI Fellowship proves again and again that when you put the right mentorship and infrastructure around brilliant, driven students, the results are extraordinary. Parents often ask how YRI students are producing work that outshines even graduate-level projects. The answer is simple: YRI treats high schoolers like real researchers, providing them with the tools, guidance, and expectations of professionals. That environment transforms them into innovators who can take on the hardest problems facing humanity.
The broader implications extend far beyond Aarnav’s individual success. If a high school student, under the right mentorship, can produce a model that rivals clinical tools, it suggests that the boundaries of who can meaningfully contribute to science are shifting. Youth are no longer passive learners waiting to enter academia they are becoming active participants in the research landscape, pushing the boundaries of knowledge in ways that could save lives.
As cancer researchers worldwide continue their search for reliable early detection methods, Aarnav’s AI-powered approach offers a glimpse of what the future may hold: diagnostics that are faster, cheaper, more accurate, and universally accessible.
If you want your student to publish in top journals, win international science fairs, and launch world-changing innovations while still in high school, the opportunity is here. Apply now to the YRI Fellowship at yriscience.com.