Why High School Pre-Med Students Should Embrace Data Science & AI
By Priya Parthasarathy | Co-Founder, DIYA Research
My daughter had always dreamed of becoming a doctor. As she entered high school, her focus sharpened: she wanted to gain admission to a pre-med focused undergraduate program. Naturally, she began thinking about what experiences could make her application stand out. She’d heard from peers and counselors that summer activities like shadowing physicians, volunteering at clinics, or working in research labs were the gold standard for aspiring pre-med students. She was determined to follow this path, but finding lab opportunities proved much harder than sheexpected. Despite her enthusiasm, access to labs were limited, and shadowing programs were highly competitive. As a parent, I wanted to help her explore meaningful alternatives. Having spent over 25 years in the software and hi-tech industry, I’ve seen how technology has revolutionized every field — including medicine. I suggested she look into data science as a way to pursue impactful research. Initially, she was hesitant. Data science seemed unrelated to her goals, but I assured her it was a powerful tool for solving complex problems, including those in medicine.
This suggestion turned out to be a pivotal moment in her journey. Under the guidance of a bioinformatics professor, she began analyzing publicly available datasets to study uterine cancer markers. Without stepping into a traditional lab, she uncovered meaningful patterns in the data and contributed to impactful research. This experience not only deepened her understanding of medicine but also helped her realize how vital data science is in addressing some of healthcare’s biggest challenges.
In this blog, I’ll share why data science is a game-changer for pre-med students, how it’s shaping modern medicine, and how organizations like DIYA are empowering students to excel in this growing field.
Data Science and Its Role in Modern Medicine
Medicine today is driven by data. Advances in technology have enabled researchers to collect and analyze vast amounts of information, leading to groundbreaking discoveries. For pre-med students, understanding how to work with this data can open doors to exciting research opportunities and prepare them for the future of medicine.
Here are some ways data science is revolutionizing healthcare:
1. Epidemiology and Public Health
Tracking the spread of diseases and assessing the effectiveness of interventions requires analyzing large-scale population data. For example, during the COVID-19 pandemic, data science tools were essential for predicting infection rates, identifying at-risk populations, and evaluating vaccine efficacy.
2. Genomics and Personalized Medicine
Genomic research relies heavily on data science. By analyzing genetic data, researchers uncover the causes of hereditary diseases and develop personalized treatments. Tools like machine learning help scientists sift through massive datasets to identify patterns that would be impossible to detect manually.
3. Clinical Trials and Treatment Outcomes
Data science is used to evaluate the safety and efficacy of treatments by analyzing patient data from clinical trials. Predictive models also help doctors personalize treatment plans, improving patient outcomes.
By learning data science tools early, pre-med students can position themselves to contribute meaningfully to these areas. More importantly, they gain a versatile skill set that extends far beyond traditional medical research.
Data Science in Action: Empowering Pre-Med Students
My daughter’s experience isn’t unique. Many students, especially those pursuing pre-med, feel limited by the need for physical labs or shadowing opportunities. However, data science provides an accessible and impactful alternative.
Here are some ways pre-med students can apply data science to their research:
1. Public Health Analysis
Students can explore publicly available datasets to analyze healthcare trends. For example, they might study vaccination rates, assess disparities in healthcare access, or examine the impact of socioeconomic factors on health outcomes.
2. Genetic Research
Using platforms like Ensembl and NCBI, students can analyze genetic data to investigate hereditary diseases or explore the evolutionary basis of certain traits.
3. Disease Modeling
Students can use data science tools to study disease prevalence, investigate correlations between environmental factors and health, or predict treatment outcomes.
These projects don’t require physical labs — just access to data, curiosity, and the right guidance.
DIYA’s Research and Summer Programs: Empowering Students with Data Science Skills
Research Programs: Tackling Real-World Challenges
At DIYA, we believe that high school students are capable of making meaningful contributions to some of the world’s biggest challenges. That’s why our research programs offer students the opportunity to work on advanced, data-driven projects under the guidance of expert mentors, including researchers and academics from prestigious institutions.
Our research topics span a wide range of domains, from healthcare and genomics to social sciences and environmental studies. For example, one of our pre-med student groups conducted a project under the mentorship of a Stanford University School of Medicine scientist. They used machine learning models to analyze breast cancer risk factors, resulting in a professionally published research paper — a remarkable achievement for high school students.
Participating in these programs allows students to develop critical thinking skills, collaborate on impactful projects, and produce tangible outcomes, such as journal publications or conference presentations. These accomplishments not only strengthen college applications but also prepare students for future academic and professional pursuits.
Summer Programs: Building the Foundation for Research
To thrive in today’s data-driven world, hands-on programming skills and a strong foundation in data analysis are essential. DIYA’s summer programs are thoughtfully designed to equip students with both the technical expertise and the mindset needed to work effectively with data.
Our camps focus on cultivating a data mindset — the ability to analyze data, uncover patterns, and draw meaningful insights. Non-coders are introduced to user-friendly tools like Tableau, enabling them to explore data visually and derive actionable insights. For students interested in coding, we start with Python programming, gradually advancing to exploratory data analysis and predictive modeling. With a curriculum designed for all skill levels, these camps empower both beginners and aspiring coders to confidently tackle real-world datasets.
Through hands-on projects, students delve into real-world topics such as public health trends, social issues, and environmental challenges. This approach not only teaches them the mechanics of data analysis but also highlights how data can be leveraged to solve problems and drive decisions across various fields.
A Gateway to the Future: Why Programming Matters
Many pre-med students hesitate when it comes to programming. They often think, “This isn’t for me — I want to work with people, not computers.” I’ve heard this sentiment many times, and I completely understand. But as someone who’s worked in the tech industry, I believe programming is an invaluable skill for any future professional — especially in today’s world where AI and data are ubiquitous.
Think of programming as the English of the digital age: just as learning to write helps you express your ideas, learning to program helps you analyze and communicate with data. Whether you’re analyzing clinical trial results or studying genetic datasets, the ability to write even a few lines of code can give you the power to uncover insights, back up your findings, and create impactful research.
For pre-med students, programming isn’t about replacing their passion for working with people — it’s about enhancing it. Including data analysis in journal papers, whether as a student or a professional, can significantly strengthen the impact of their work. And with today’s advances in AI, programming has become easier than ever to use. However, a solid understanding of Python basics is crucial to harness these tools effectively.
Conclusion: A Call to Embrace Data Science
Data science is more than just a tool — it’s a gateway to discovery and innovation. For high school pre-med students, it offers the chance to engage in meaningful research, develop critical thinking and technical skills, and stand out in a competitive field. But its impact extends beyond medicine. Whether you’re interested in healthcare, engineering, social sciences, or any other domain, the ability to work with data is a transformative skill that opens doors to countless opportunities.
If you’re a student eager to explore new opportunities, a parent looking to support your child’s aspirations, or a teacher guiding young minds, consider how data science can reshape the journey to success.
Author: Priya Parthasarathy, Co-Founder at DIYA Research Inc.
Padmapriya is passionate about bringing data science into education and helping teachers empower their students with essential skills for the future.
DIYA Research empowers youth with data science and AI skills through hands-on projects and strategic partnerships. By bridging the gap between theoretical knowledge and practical application, we prepare future leaders to tackle global challenges, drive innovation, and build workforce readiness. Learn more about our initiatives at https://diya-research.org.
