ML-generated screening scripts use question-level evaluation metrics to cut trial setup time while improving candidate accuracy and engagement.
Mean-variance weighting and generative models tailor clinical assessment items to cut score variance and improve treatment-effect detection.
Sensor, anamnesis, and medication data drive automatic question selection, making patient surveys more personalized and less time-consuming.