Still have questions?
What happens after I apply?
We’ll schedule a short call to confirm that this package is suitable for your goals. Then I’ll send over a contract. Once you submit your payment, you’ll receive an email with a link to a questionnaire that I’ll use to begin scheduling interviews with some of your team members.
Will you sign an NDA before we start?
The contract for this ML Domain Shift Assessment will include confidentiality and non-disclosure provisions.
Can’t we just gather a larger training set?
If you’re able to do this, go for it. But the key is not only a larger dataset – diversity is critical. You need to understand the variations in your data and what subpopulations are underrepresented in order to focus your data collection efforts. For many medical applications, it’s not possible to cover all sample preparation techniques, scanners, and patient populations. The alternative is to narrow the scope of your product. But there will still be variations, even with samples imaged on a single scanner. This assessment will help you understand those variations and guide how you handle them.
We haven’t even started training models yet. Is it too early to think about generalizability?
No, it’s not too early to think about it. If you’re getting ready to start acquiring data, you want to be thinking about ways to reduce the sample processing and image acquisition variations. If you’re scanning your own slides, you might be able to include a color calibration step in your process to reduce variations from different scanners. You should also be thinking about the patients in your training set and how you might obtain one or more external cohorts for testing. These are all topics covered in the assessment.
We’ve already analyzed our datasets and understand the domain shift challenges. We just need help making our models more generalizable.
If you’ve already completed this analysis, you might consider starting with my ML Domain Generalizer instead. The focus of that service is on identifying and applying advanced data-, image-, and model-centric approaches to improve model generalizability.
Our project is different from other applications. It’s not just H&E histology. Is this a problem?
No. If you’re using something other than H&E or you’re developing a novel medical imaging device, it’s even more important to analyze the variations in your data. Less common modalities are less understood, so we might need to dig a little deeper to identify the sources of variation.
What’s next after the assessment? Can you help us with implementation?
After completing this assessment, we have a few options. Your team could go off and implement the recommendations outlined independently. However, my clients have found that their projects are completed more efficiently with continuous guidance. You can sign up for my Advisor service and receive advice as your team progresses. If, after implementing the first line solutions to improve generalizability, you find the need for more advanced approaches, my Domain Generalizer is a good choice.
Still not sure if this is the right package for you?
Schedule a free Strategy Session, and I’ll help you determine if this is a good fit.