How can I leverage programming/coding knowledge in medical school/research

[haikuhero]

Hey all,

Wanted to see if my skill set could be of much use as I enter medical school.

I have about 10 years of experience in software development. I want to see if I can leverage this to my advantage in medical school.

The most obvious direct benefit would be getting involved in some research that might take advantage of a background in coding (crunching a lot of numbers, creating panels, databases, computational simulations, etc.)

For example, I already have a publication due for creating a web application tool for directly hooking into the NCBI (Home - Gene - NCBI) database that is used in some ongoing bioinformatics research.

Has anyone heard of similar happening? Or related uses of my programming background?

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[LIFS7]

The skill set of coding to run statistics for research projects would get you many opportunities.

 

[yandorio]

Here's my advice. Get acquainted with BASIC. It will be the medical language of the future.
For example you could input patient data with line 10 input X$.
Then you can add string variables a la line 20 Y$=X$+Z$
then at the and you can return. line 30 goto 10, creating what is called a "loop." From there you can go on to Turbo BASIC. I would also be willing to discuss FOR and NEXT functions if you are serious.

 

[haikuhero]

Here's my advice. Get acquainted with BASIC. It will be the medical language of the future.
For example you could input patient data with line 10 input X$.
Then you can add string variables a la line 20 Y$=X$+Z$
then at the and you can return. line 30 goto 10, creating what is called a "loop." From there you can go on to Turbo BASIC. I would also be willing to discuss FOR and NEXT functions if you are serious.

With the niche BASIC provided for that has been improved upon in future langs/it's continually declining popularity (TIOBE Index - TIOBE) since the 1990s that has "... hobbyist scene for BASIC more broadly continues to exist" I can't imagine that it would be a language of the future...

At best, it would be a language to maintain some legacy code like how COBOL is used for banking software because it would be too expensive/risky/difficult to upgrade from 1960s code bases.

 

[haikuhero]

What kinds of things did you work on when you were a software developer?

- Front end designing
- Creating, managing, writing to Databases for applications
- User authentication
- Reports
- Map Integration
- Custom Content-management systems (think blogs)
- Custom User interactions system (think forum software)
- Chat software
- Server administration/Deployment (in Linux)
- Integration with specific business hardware like specialty printers
- Integration with APIs (automated text messaging, emailing, etc.)
- Networking
- eCommerce with secure checkout and automated 3rd party vendor payout (so user could create storefronts and get paid for it)
- Complex GUIs like calendar management systems
- Complex system building like scheduled QA, generative invoicing with eSign features
- Statistical analysis
- Integration w/ cloud services (Ex. AWS & DO)
- Some basic AI stuff recently (image recognition, voice cloning)

 

[Mr.Smile12]

Ask the Student Research office?

 

[yandorio]

With the niche BASIC provided for that has been improved upon in future langs/it's continually declining popularity (TIOBE Index - TIOBE) since the 1990s that has "... hobbyist scene for BASIC more broadly continues to exist" I can't imagine that it would be a language of the future...

At best, it would be a language to maintain some legacy code like how COBOL is used for banking software because it would be too expensive/risky/difficult to upgrade from 1960s code bases.

Sorry, I was being cheeky. Next thing I was gonna try to sell you my TRS-80.
On a serious note I was part of the Bioinformatics boom of the 90's and watched people like Pearson and Lipman,
or Altschul, come up super popular pattern recognition tools like BLAST. Maybe you could update their old tools with new tricks
or come up with some sort of 21st century genome browser or learning tool for students. Interestingly ab initio structure prediction was figured out by google wizards a few years ago--something many of us never thought would happen in our lifetimes.

 

[operaman]

Tons of ways. If you can develop some kind of specialized knowledge or application you can get yourself looped in to all sorts of projects.

I knew a guy in med school who got reallly good at using the SEER database, which basically tracks oncologic outcomes data nationally. He got really good at using it and running stats on the raw data, so he got slapped on every student SEER database project we ever did. It was about 15 pubs by the end of med school just from SEER studies. They’re great student projects since they require no IRB and are basically formulaic - either pick some rare obscure cancer in your field of choice and then write about whatever interesting stats findings you get from your analysis, or look back for any similar database study more than 20 years old and do an update. Given the recent advances in cancer treatment could possibly update even more recent ones.

So that’s just one example of many. Having people that really get AI and can build DCNNs or LLMs would be highly valuable. The fact you can potentially speaking both the language of medicine and the language of coding would make you highly prized. My last DCNN projects were always hindered because the computer guys didn’t always understand the sorts of clinical issues I wanted to use the AI to solve, or the nuances of the kind of clinical data we wanted to feed it. Someone who can speak both would have been amazing.

Really, sky is the limit. If you have a useful skill it won’t take long to find places to deploy it. Once you have a sense what fields interest you, seek out mentors doing the kind of work where your skills might be a big help.

 

[differentiating]

I was able to do summer research where I was the one doing the primary data analysis (using R) in med school, and was able to get on a paper that way. I have a line on my CV for "skills" where I included the coding languages I was familiar with, and while R was one I learned on this project, my familiarity with others was what helped convince my PI to take me on.

Depending on what field in medicine you're interested in, I'm sure you can find researchers willing to take you on and make use of your much more extensive background.

 

[lildong]

I was a FAANG software engineer prior to medical school. Having a programming background helps so much but I highly recommend also learning stats (t-tests, logistic regression, chi-square etc.) as well because that's a necessity for pubs.

 

[HappyRabbit]

Mainly clinical research but it's highly lab/project dependent. There are plenty of labs that need help with Python data pipelines or want to automate manual work that's being done. Just reach out to a ton of labs and you'll be able to find a niche that lets you leverage your experience.

 

[xavi22]

I have MD and software development experience. It is a blessing and a cause; during residency, I tend to notice lots of inefficient processes that a simple if, else loop function can fix/automation. These days, I mostly code in python, R etc, and integrate LLM/ML/AI in my codes.

The combo is indeed a beauty. With the advent of synthetic data for training LLM, agentic models etc, the only limitation is your creativity. We are building amazing projects. Interesting times ahead for sure!

 

[MD-PhD-NonTrad]

Literally just knowing basic Python graphing and statistics (SciPy, Pandas, SeaBorne) is a cheat code to high med student research output. When a resident/MD faculty reaches out for med student research help, it is almost always a combination of organizing data they already have or doing simple chart review. If they hand you a spreadsheet, they are assuming it will take you 40 hours to clean it up and organize it to produce a few graphs and statistics. With basic programming, you can do it in 2 hours or less. If you have 10 years of software development, your skills may even be far above literally anything faculty will actually need.

If you want to get involved in like an actual research project rather than standard med student research, med students that can do dry lab projects for summer research projects are worth their weight in gold. Or doing data analysis for any wet lab. If you show up to any lab saying “What data do you have and what do you want me to do with it” they will love you.

You can obviously help earn brownie points with organizing lab websites, making posters or things look pretty, etc. but from a productivity perspective it is fantastic.

I used coding in my research by taking a couple weeks to develop an image processing pipeline for an assay my lab uses for everything. A week of development, now they send me 100 images, I press go, I sent the stats, I get on the paper. I am also now automating a chart review process just because I can. I use it in a med school capacity to programatically generate study guides and practice questions from lecture/step materials using LLMs. Genuinely it is something that just sets you apart in every way you can.

 

[xavi22]

I am actually building a uworld alternative using finetuned LLMs with knowledge base that recursively learns from the user's corrects and incorrects, and presents next 40 questions based on that. Think of it as anki but on steriods lol and this is just an MVP.