I thoroughly enjoyed reading your personal statement for application to Stanford’s master’s program in data analysis. Your story about working as a physician and realizing the applicability of data analysis to healthcare is very compelling. You have plenty of experience and demonstrated interest in the program you are applying for, and you do a nice job of focusing on yourself and why you would be an excellent candidate for this specific program. Since your content was so solid, I spent my time reorganizing your essay to focus on your individual story. While there will be many equally qualified candidates applying, the ones who can describe their background and motivation in the form of a compelling narrative are the ones who will catch the eyes of the admissions officer. Your anecdote about working in the hospital and not knowing how to treat your patient was incredibly interesting, so I chose to foreground it in your essay.
- Personal storyを一番始めに→インパクトが出た
- フォーマットの修正（Western academic settings: 12pt font, double-spaced, left justified, with one inch margins）←そんな明確に知らなかった！
After university, I started working as a clinical physician. Working as a physician was rewarding, and at first I felt proud just by prescribing treatments recommended in research papers.
My interest in data analysis began in a hospital room. One day during my residency, I encountered a young male with intraventricular thrombus who had developed an acute cardioembolic stroke.
Statement of Purpose
My interest in data analysis began in a hospital room. One day during my residency, I encountered a young male with intraventricular thrombus who had developed an acute cardioembolic stroke. Working as a physician, I prided myself on prescribing treatments based on the latest research, but the role of immediate anticoagulation in this case was controversial. As usual, I turned to scientific papers to research his illness, but the randomized control trials described did not apply to the patient at hand. He was significantly younger than the studied population, and his medical history did not meet the inclusion criteria of these studies. I became perplexed. How on earth could I choose the optimal treatment for this patient?
Physicians cannot always provide tailored, optimal, and evidence-based treatment for each patient—and as the person responsible for my patients’ health, I found this very upsetting. Although I have long had an interest in the crossroads of healthcare and information technology, this was the watershed moment where I realized the ultimate goal of my career: enhancing people’s well being through individualized healthcare data analysis. Accumulating and analyzing a vast amount of individual healthcare data could make more optimal and personalized healthcare possible.
With my programming tools and work experience, I wanted to do something to help patients through the application of personal data. This turned into my next project, a software application called Flixy, launched on July 2015, which I designed to raise patients’ drug adherence. The program synchronizes a drug case with a mobile app via Bluetooth, automatically recording the patients’ drug intake.
My exposure to big data medicine during my internship led me to research more emerging medical revolutions made possible by big data analysis. Big data analysis, combined with machine learning methodologies, enables personalized, actionable predictions. It can play a crucial role in reducing medical uncertainty, like the uncertainty I experienced in the hospital that day with my young patient. Unlike other fields, the medical field must show not only correlations but also cause-and-effect relationships, and expert medical knowledge is required to reveal confounding factors between two variables. Therefore, medical professionals engaging in the data analysis field would be remarkably valuable.
Stanford’s program excites me because of the laboratories there engaging in research that aligns with my interests. The labs of professors Wong, Hastie, and Tibishirani, with their research in phased genome analysis , statistical modeling and prediction in medicine, and modeling of interactions between treatment and covariates, seem particularly well suited to my intellectual goals. The program curriculum goes far beyond general statistics courses, with specialized courses in analytics for big data and data driven medicine. Stanford students’ access to Amazon’s EC2 cloud platform is another big draw for me; the opportunity to do large-scale computing, necessary for analyzing big data, is rarely found in Japan. Finally, the internationally high reputation of your department attracts diverse, top-notch students, and studying in this unique environment will lead me to think creatively and push myself further than I might otherwise.
After completing my degree, I plan to use my increased knowledge to engage the healthcare IT industry and create a system that automatically evaluates disease risk from patient data. This system would extract similar cases from accumulated data and predict what physicians would want to evaluate in a new case. A tool that could calculate disease risks, optimal treatment, and prognosis from patient data such as age, sex, physical data, and preexisting conditions would revolutionize evidence-based care. Stanford is a home for people who want to turn complex ideas into reality, and this is why I seek a place in your esteemed department.（704 words）