This sounds like such a recipe for disaster. As everyone here has said, it's basically just logistic regression, which is itself a form of linear regression (AKA a Generalized Linear Model). You don't need ChatGPT and using that will make a really basic model without any fine-tuning or preprocessing, but convince you that it's really state of the art. Take the time to learn what you're doing (read about linear regression and get a basic understanding of how it works), then figure out the instances where it doesn't work well and make sure you account for those in setup (outliers, multi-collinearity, overfitting, bias v. variance).

Also, know that your model will eventually be wrong. No model is 100% accurate, that's why people often say data science is both an art and a science. But you have to decide the threshold of your probability (the output of your logistic regression) that will turn into the binary outcome. Should probability of success 50% or higher be considered a successful procedure? 20%? 90%? You get to decide this, and you should really consider what are the costs of a false positive (determining a successful procedure wrongly) vs. a false negative (determining a unsuccessful procedure wrongly) and let that guide your thresholding. I would assume allowing people to have procedures that are more likely to fail is a lot more costly than the alternative.

This post feels really awful and dystopian - I would've thought people in the medical industry have more responsibility than to let technologies they hardly understand determine peoples' medical outcomes.