[rjcrystal]

I work in healthcare domain, We've had great success converting printed lab reports (95%) to Json format using 1.5-Flash model. This post is really exciting for me. will definitely try out 2.0 models.

The struggle which almost every ocr usecase faces is with handwritten documents(doctor prescriptions with bad handwriting) With gemini 1.5 flash we've had ~75-80% percent accuracy (based on random sampling by pharmacists). we're planning to improve this further by fine-tuning gemini models with medical data.

What could be other alternative services/models for accurate handwriting ocr?

[myaccountonhn]

> We've had great success converting printed lab reports (95%) to Json format using 1.5-Flash model

Sounds terrifying. How can you be sure that there were no conversion mistakes?

[Havoc]

How on earth is anyone ok with 75% accuracy in prescriptions context?!? Or medical anything

That’s literally insane

[martimchaves]

I'm guessing that human accuracy may be lower or around that value, given that handwritten notes are generally difficult to read. A better metric for document parsing might be accuracy relative to human performance (how much better the LLM performs compared to a human).

[knowaveragejoe]

Nobody said they're okay with it, nor did they describe what they use the data for.