Growth-Oriented Essay: Curiosity can be seen in many ways. Please share an example of how you have demonstrated curiosity and how that has influenced your growth. (up to 250 words)
Background Information: The applicant, a Machine Learning (ML) entrepreneur specializing in healthcare diagnostics, shares how his curiosity to learn other ML algorithms’ evolution in diagnosing Alzheimer’s, cancer, and heart disease transformed his platform into a global community.
Curiosity: Machine Learning
Curiosity (Explained): Technical narratives in MBA application essays rarely work. For the essay, the applicant shares one example where a community member – a doctor in Kenya suggested a ML solution for a US doctor to avoid burnout. The suggestion led to a study on the IMPACT of AI in diagnostic and cost saving for the US government in rural healthcare.
MBA Essay Strategy: I wanted to show the applicant’s contributions in diagnostic from 2020 to 2024 by citing two events. Such examples build credibility instead of engagements that were recent. The evolution of the platform from an AI development community to a community for discussing the application of AI in diagnostics is captured through a ‘curiosity’ angle.
Theme: Healthcare
Theme (Explained): AI in any industry is controversial if the utility is not captured in a precise manner. Here, the healthcare and AI applications are captured from three angles – reducing healthcare costs for the government, avoiding burnout for doctors, and the life-saving utility of intelligent dashboards in diagnostics.
Profile: Entrepreneur
Industry: Healthcare
Opener: The opener takes the reader to the career choice question he faced as a young person before transitioning to his first engagement in healthcare, where an ‘intelligent dashboard’ he developed saved hundreds of lives.
Sample Harvard MBA Curiosity and Growth Essay – Creating a Global AI in Healthcare Community (248 Words)
Doctor or Engineer – this was a question I used to hear growing up. I would annoy my parents with the answer ‘detective,’ but the answer ironically became a mantra in when I was volunteering to shift high-risk patients from homes to hospitals. The decision was based on diagnostic data, distance from home to hospitals, and, most importantly..
After four years of iterative development in AI diagnostics, I was curious to know how international machine-learning communities specializing in healthcare diagnostics were progressing...
...
....
