Deciding what to focus on

For the past couple of years, my rough modus operandi has been something along the lines of… “to build deep technical skills and understanding in machine learning (and computer programming more broadly)”.

The rough end-goal has been to become a doctor who can build machine learning models, and thus be uniquely-positioned to incorporate my medical insight when building them.

I feel this has served me well until now. But it’s also low-resolution.

Building “a machine learning model to be applied in medicine” could mean many things. There are many types of machine learning models and there are many medical problems.

I’ve decided I’m going to start switching my focus towards more specific areas and use-cases, and really hone in where there is the most value to be had.

To do this, I’m planning to do a series of ‘deep dives’ over the next several months, with the intention of iteratively moving towards the areas that I will devote wider attention.

After a quick, rough brainstorm, the following areas have made it onto my initial list for exploration:

• Facilitating incorporation of machine learning into healthcare (perhaps predictable if you’d followed this newsletter for a while.. 😉)
• Biological information processing (bioinformatics, drug discovery)
• Intelligent knowledge management (extracting information from research, personal knowledge management)

I have various ideas within each of this, which you can see here if interested. I’ve also thought about some tentative next steps in each area.

This isn’t a complete list, just a first draft. I’m planning to update and grow this over time, and to proactively reach out to people for suggestions and deep conversations in coming months.