Your statement is very good. I made some English corrections, and made a comment about one section in the text. I’ve attached my revised version.
Finally, I have one suggestion for the overall content of your statement:
I believe you are a unique candidate because you are a practicing Japanese physician, and I guess there will probably not be many other students like you in the program. It might be a good idea to discuss some aspects of this, such as:
– Do you plan to work in Japan or the US (or both) in the future?
– Why is Stanford the best option for you from the perspective of a Japanese physician and data scientist?
– How is data science studied and applied in the Japanese health care system, and how will studying at Stanford broaden your perspective/knowledge?
This was the thought I had when reading your letter, but it is very good as it is now. If you would like to add some content, I will check it again.
Please let me know if anything is unclear, and feel free to contact me whenever.
Enhancing people’s wellbeing through individualized healthcare data analysis is the ultimate goal I aim for in my professional career. By accumulating and analyzing a vast number of individual healthcare data, I believe that optimal and personalized healthcare information feedback is possible. I seek to attain this goal through working as a data scientist with a medical background.
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. I searched for papers whenever I encountered clinical problems, and I came to believe undoubtedly that having a medical paper supporting a clinical decision is the most important thing in clinical practice. One day, I encountered a case of a young male with intraventricular thrombus having developed acute cardioembolic stroke. The role of immediate anticoagulation in this case is controversial. As usual, I did some research and found papers on this matter. However, as I critically read these papers, I noticed that the randomized control trials described in these papers were not applicable to the patient at hand. This patient was significantly younger than the studied population, and his race was different. Moreover, his past medical history did not meet inclusion criteria of these studies. I became perplexed. How on earth can I decide optimal treatments for this patient? Medical papers I had relied on so far did not back up me in this case. I am still not sure whether I provided optimal treatments for this patient. During my residency, I often encountered similar cases. Physicians nowadays cannot always provide personally-tailored, optimal, and evidence-based treatment for each patient—and I found this very upsetting. Treatments recommended by randomized control trials are mostly one-size-fits-all models. External validities such as race, age, or preexisting conditions are often not brought in to consideration; thus, evidence provided by clinical trials does not always prove a treatment’s effectiveness on all patients.
Coincidentally, I came across the concept of big data driven medicine in a TV program. It described a big data driven system that predicts baby infection in a neonatal ICU. I was struck by this introduction to big data medicine, and became increasingly interested through researching more about the emerging medical revolutions made possible by big data analysis. I have also read that big data analysis, combined with machine learning methodologies, enables personalized, actionable predictions. Therefore, I now strongly believe that big data analysis can play a crucial role in reducing medical uncertainty. My acquiring more profound knowledge on data analysis is imperative in achieving my goal. I also believe that a medical professional engaging in the data analysis field would be remarkably valuable for the field.
I became deeply interested in Stanford’s program because there are several laboratories that share similar interests with me, particularly the labs of professors Wong, Hastie, and Tibishirani. Furthermore, this program offers not only general statistics courses, but also domain-specialized course, which is unique to this graduate school. The courses “Analytics for Big Data”, and “Data Driven Medicine” are especially relevant to my interests. Furthermore, the internationally high reputation of the department attracts diverse and competent students, and I believe studying in this environment will be very stimulating and exciting.
After completing my degree, I plan to engage in the healthcare IT industry, and create a system which automatically evaluates disease risk from patient data. This system calculates the disease risks, optimal treatment, and predictive prognosis from patient data such as age, sex, physical data, and preexisting conditions. It would also extract similar cases from previously accumulated data and predict what physicians would want to evaluate in the new case.
I look forward to joining Stanford University as a graduate student in your esteemed department, which would be a great step towards my ultimate goal.