Artificial intelligence (AI) has reshaped cancer research, opening new ways to tackle one of the most complex diseases. It has enabled more accurate diagnoses, more personalized treatments, and a deeper understanding of how cancer works. If you’re a high school student drawn to the intersection of technology and oncology, this is an exciting field to explore. These projects let you apply AI to real cancer research challenges while building valuable skills.
Many high school science fairs welcome innovative projects on critical issues like cancer. The ideas below are tailored to high schoolers, focusing on AI applications that don’t require advanced technical knowledge but still offer room for real discovery. You’ll work with real-world data, collaborate with peers and mentors, and build skills in coding, data analysis, and scientific research.
Why research?
Research is how we understand the world and solve hard problems. Doing it builds critical thinking and teaches you to ask meaningful questions. It lets you explore topics you care about and uncover new information. You’re not just learning, you’re adding to a broader understanding of your field and maybe making a difference in it.
Top 9 AI and cancer research ideas
In high school you likely have access to basic programming resources and online AI tools, which makes this a great time to start. These projects are meant to inspire you to apply AI in meaningful ways, whether that’s analyzing medical images, predicting cancer risk, or uncovering new treatment options.
1. Cancer diagnosis
Explore how AI can help diagnose cancer. Investigate AI-based diagnostic tools, like machine learning algorithms that analyze medical images, and assess their accuracy against traditional methods. You could focus on one cancer type, such as breast or lung cancer, and analyze how AI identifies abnormalities in imaging scans. Summarize your findings in a report on the benefits and limitations of AI-based diagnosis.
2. AI in cancer treatment planning
AI can help plan cancer treatment by analyzing patient data and suggesting personalized plans. Explore how AI algorithms optimize treatment, weighing factors like tumor size, location, and patient health. You could analyze case studies where AI improved outcomes and propose your own algorithm to guide treatment decisions.
In 2018, Rishab Jain developed a machine learning algorithm that tracks the pancreas in a patient’s scans so radiotherapy can target the tumor as accurately as possible. He won the title of America’s Top Young Scientist at the 3M Young Scientist Challenge (and $25,000).
Learn more about how he did it in this video:
“In the radiotherapy treatment where radiation is applied to kill tumor cells, my tool tracks the pancreas in the scan itself,” Jain explains. “When the radiation hits, it hits the pancreas accurately and efficiently so it can help treat the tumor much more effectively.”
Time
3. AI for drug discovery
AI is accelerating the search for new compounds that could treat cancer. Explore how AI algorithms scan large databases to find promising drug candidates, and look at techniques like deep learning and natural language processing. Present your findings, focusing on AI’s impact on the speed and cost of developing new cancer drugs.
4. Cancer prognosis
Prognosis is a critical part of cancer care, and AI can help predict outcomes from many factors. Explore how AI models analyze patient data to estimate survival rates and recurrence risk. You could study specific models used in clinical settings, how they’re trained and validated, and even build your own prognosis model from existing datasets.
5. Cancer genomics
Cancer genomics studies the genetic changes behind cancer, and AI can help analyze large genomic datasets. Investigate how AI tools identify cancer-linked mutations and guide personalized treatments. Explore specific software platforms and their role in genomic analysis, then propose new ways AI could deepen our understanding of cancer genomics.
6. Cancer patient monitoring
Monitoring patients is crucial for tracking treatment and catching recurrence. This project looks at how AI can streamline monitoring by analyzing health records, imaging, and other data. Investigate AI applications that alert clinicians to significant changes for early intervention, and discuss the advantages, challenges, and ways to improve them.
7. Cancer risk assessment
AI can assess cancer risk from lifestyle, genetics, and environmental exposures. Explore how AI models predict risk and flag individuals who could benefit from preventive measures. Analyze different risk-assessment tools and their accuracy, and propose a new model that integrates multiple risk factors for better predictions.
8. AI in cancer immunotherapy
Immunotherapy is an advanced cancer treatment, and AI can help develop and optimize it. This project examines how AI designs new immunotherapies, such as CAR T-cell therapy, by analyzing large datasets and identifying potential targets. Explore AI that predicts patient responses and suggests personalized treatments, and discuss AI’s impact on the future of immunotherapy.
9. Cancer screening
Early screening is key to successful treatment, and AI can improve its accuracy. Explore how AI algorithms analyze medical images or patient data to detect early signs of cancer. Examine specific AI screening tools, such as those used for mammograms or colonoscopies, and discuss their sensitivity and specificity. You could even develop a new AI screening model to improve early detection.
Gopalaniruddh Tadinada and Rishabh Ranjan won the H. Robert Horvitz Prize at ISEF in 2023 ($10,000) for building a custom, automated system to detect gastrointestinal cancer before serious symptoms appear. Their system combines robotics and machine learning to analyze blood samples and identify healthy patients, as well as those with pancreatic, colorectal, or hepatic cancers, in only three hours at an estimated cost of about $300.
“This project aims to improve early GI cancer detection through the analysis of serum miRNAs with a custom built, automated, end-to-end system: CanDELA. CanDELA uses a magnetic bead based miRNA extraction apparatus to extract miRNAs from patient whole blood samples, and an automated peristaltic pump based liquid handling robot to synthesize an appropriate solution for cDNA synthesis.”
Society for Science
Final thoughts
These nine ideas give high schoolers a range of ways to explore AI’s role in cancer research. Whether you’re interested in diagnosis, treatment, or genomics, they offer a solid foundation for a science fair or passion project, combining technology and oncology to take on one of the most critical health challenges of our time.
Want to elevate your project but aren’t sure where to start? Take a look at Rishab’s free STEM student guide, full of practical advice for students aiming to take a project all the way to the international level. It covers planning and conducting research, presenting your project, and finding strong opportunities in STEM.
Leave a Reply