
Smarter Cancer Detection Starts Early.
Explore how AI and cancer research can help detect cancer earlier and healthcare more accessible to people in rural Arizona.
AI. Research. Early Detection. Better Access.
Mission
Use AI and cancer research to support earlier detection and better access to care.
Community
Share simple cancer awareness and screening information with families, especially in rural Arizona.
Resources
Make cancer, screening, and AI in healthcare easier to understand through clear educational content.
Collaborate
Connect with doctors, researchers, students, and community groups working toward better cancer care.
About Me
My name is Anish Thirukumaran
I’m Anish, a high school senior interested in cancer research, medicine, and artificial intelligence.
My work has included computational cancer research at the University of Arizona, where I studied miRNA and quiescent cells under Dr. Guang Yao. I also completed NASA GeneLab research using omics data to study how spaceflight affects the spleen.
Outside research, I have spent significant time in clinical settings through NICU volunteering at Banner Desert Medical Center and physician shadowing with Dr. Austin Traasdahl. These experiences helped me understand both the science behind disease and the real needs of patients and families.
I also participated in the Mark Cuban Foundation AI Bootcamp, where I worked on an AI-based medical diagnosis and treatment app.
Together, these experiences shaped my interest in one area: how technology and research can help detect cancer earlier and improve access to care.

Research
Computational Cancer Research — University of Arizona
Through the KEYS Research Internship, I conducted computational cancer research under Dr. Guang Yao. My work focused on miRNA regulation in quiescent cells and how disruptions in these processes may contribute to cancer development.
NASA GeneLab Research
Through NASA GeneLab for High Schools, I completed a capstone research project using omics-based data to study how spaceflight affects the spleen. This experience strengthened my understanding of how large biological datasets can be used to study complex changes in the human body.
Arizona State Science Fair Project
Modeled how lung cells may detoxify 6-Nitrochrysene, a cancer-causing environmental pollutant, using molecular docking. Used AI-based programming, PyRx, and molecular modeling tools to study how the carcinogen interacts with lung cells and found evidence of multiple defense mechanisms involved in detoxification.
AI-Based Healthcare Project
Through the Mark Cuban Foundation AI Bootcamp, I worked on AI-based healthcare projects and developed an AI-powered medical diagnosis and treatment app. The project showed me how artificial intelligence can support earlier detection, improve decision-making, and expand access to healthcare.
Leadership
Mark Cuban Foundation AI Bootcamp
Served as a student ambassador in an alumni network of more than 500 students. Worked on an AI-based medical diagnosis and treatment project.
Taekwondo
As a 3rd Degree Black Belt and paid instructor, I have taught and mentored classes of up to 30 students.
Math & Science Tutoring
As a Schoolhouse tutor, I ranked in the top 10% of international tutors and helped learners across five countries.
Healthcare and Medical Experience
1 / NICU Volunteer
Volunteer at Banner Desert Medical Center, supporting NICU patients and their families. My experience has exposed me to the emotional side of healthcare and the needs families face during difficult moments.
2 / Medical Shadowing
Shadowed Dr. Austin Traasdahl and observed physician-patient interactions, medical cases, diagnoses, treatments, and PRP procedures.
STEM & Academic Engagement
01
Science National Honor Society (SNHS)
Participated in a community of students focused on science, academic achievement, and STEM engagement.
02
STEAM Society
Volunteered at school science events and supported hands-on STEM activities for students.
Athletics & Wellness
JV Tennis
Competed in tennis tournaments.
Baseketball
Played recreational basketball through middle and high school.
Strength and Fitness Club
Participated in weight-training activities with club members.
Arts

Chamber Orchestra / Orchestra Club
Performed at 8+ school concerts and an NBA halftime show for 15,000+ people.
Blogs
Past and Upcoming Events

Tennis & Basketball Tournaments2024New York
NASA Capstone Research ShowcaseAugust 2026NASA's Kennedy Space Center
KEYS Research Showcase & KEYS SlamJuly 2026University of Arizona
Arizona State Science FairMarch 2026Desert Financial Arena
Taekwondo Competitions & National Championships2018New York, New Jersey, Massachusetts, and UT
NBA Halftime Show PerformanceJanuary 2026Mortgage Matchup Center
Expert Interview with Dr. Austin Traasdahl

Dr. Austin Traasdahl, Family Medicine at Alexander Medical
1. From your experience as a physician, what do you see as the biggest barriers to detecting cancer early, particularly for patients in rural areas of Arizona?
Honestly, it mostly comes down to distance. If the nearest screening center is a couple of hours away, a lot of people put it off, especially when it means missing work and paying for gas. And when something does come back abnormal, getting in to see a specialist can take time.
2. How do you think artificial intelligence could help physicians detect cancer earlier, such as by identifying patterns in medical imaging, pathology, or patient data that might otherwise be missed?
The most promising use I see is as a second set of eyes. It can look over mammograms, CT scans, or skin photos and flag something subtle, so nothing gets missed on a busy day. It can also go through a chart and point out that someone with a strong family history is overdue for screening, which is the kind of thing that slips through in a 15-minute visit.
3. What challenges or risks do you think come with relying on AI for cancer detection, and how should physicians balance AI recommendations with their own clinical judgment?
The big one is that AI can be confidently wrong, especially for patients who weren't well represented in the data it was trained on. It's easy to start trusting the output too much. So I treat it as one input, and I still weigh it against the patient's history, my exam, and what they want before I act on it.
4. Rural Arizona communities can face challenges such as long travel distances and shortages of specialists. How could AI and telemedicine help expand access to cancer screening, diagnosis, and treatment in these communities?
This is where the two work well together. A small local clinic can do the screening or take the image, a specialist reviews it remotely, and the patient only makes the long drive if they truly need to. AI can help sort out who needs to be seen first. That means fewer wasted trips and faster answers for the people who need them.
5. Looking ahead, what changes in healthcare technology, policy, or medical practice do you think would make the biggest difference in reducing disparities in early cancer detection between rural and urban Arizona?
I'd start with the basics: reliable broadband and fair payment for telehealth so rural clinics can offer it. After that, mobile or community-based screening and stronger primary care as the front door. Just as important, payment for follow-up care and not only the first test, because a screening does nothing if the patient can't act on the result.
Closing the Cancer Detection Gap Through AI
Learn how artificial intelligence can support earlier cancer detection, better awareness, and more equitable access to care.
This simple checklist covers key ways AI and healthcare can work together to help identify cancer earlier and reach more communities.
Download the free checklist:
Using AI for Earlier and More Equitable Cancer Detection
Let's Talk About Smarter Cancer Detection
Are you a physician, researcher, student, educator, or community organization interested in cancer awareness, AI, or early detection?
I would love to learn from you and explore ways we can work together.
Better awareness. Earlier detection. Smarter care.









