Machine learning can add power to your analysis of pathology or remote sensing images:
- Assist expert by improving efficiency, precision, and repeatability
- Learn concepts beyond human capabilities like molecular biomarkers, patient outcomes, or treatment response directly from images
Using my proprietary process, I'll author a detailed analysis of your ML algorithms for quantifying images. This report will outline how to advance your project using the latest state-of-the-art techniques.
The report will detail each of the components below and make recommendations such as the following:
- Procedure for validating model on held out test set
- Steps for performing an error analysis to guide directions for data cleaning or model improvement
1. Discovery call
Let's hop on a call to learn more about each other. We'll discuss where you are now and where you need to go, what's working well and what you're struggling with.
2. Data and info gathering
I'll talk with your technical team about your current data pipeline and algorithms. I'll likely ask for any existing documentation, data samples, and possibly some code.
3. Report generation
Guided by the 5 components above, I'll write a report outlining the strengths of your current data and modeling approach and recommendations for further advancements. I'll meet weekly with you or your technical team via Zoom during this phase to review progress on the roadmap and answer any questions.
Upon completion of the report, we'll have a Zoom call for a final review and to ensure that you are confident in the next steps for your project.
- An understanding of the key components for success with machine learning
- A set of actions that can be implemented and tested by in-house data and ML engineers
- Confidence in the success of the project