For example, an algorithm designed to predict live birth rates from patient anti-Mülle-rian hormone (AMH) levels saw high predictive ability with low error rates. Similarly, the PIVET algorithm, aimed to personalise recombinant follicle-stimulating hormone (IFSH) dosing using input patient data such as BMI, age, and antral-follicle counts (AFC).