Yeah, these models are evaluated based on sensitivity and specificity, and ideally each would be above 90% for this type of application (making these types of models is my job)
Edit: the question of adding things like gender into predictive models is really interesting. Do you withhold information that legitimately makes it more accurate? The fact that black women have more prenatal complications is a thing - is building that into your model building in bias, or just reflecting bias in the healthcare system accurately? It’s a very interesting debate.
godset t1_j1mdxec wrote
Reply to comment by Hsinats in Machine learning model reliably predicts risk of opioid use disorder for individual patients, that could aid in prevention by marketrent
Yeah, these models are evaluated based on sensitivity and specificity, and ideally each would be above 90% for this type of application (making these types of models is my job)
Edit: the question of adding things like gender into predictive models is really interesting. Do you withhold information that legitimately makes it more accurate? The fact that black women have more prenatal complications is a thing - is building that into your model building in bias, or just reflecting bias in the healthcare system accurately? It’s a very interesting debate.