SPOT: Sequential Predictive Modeling of Clinical Trial Outcome with Meta-Learning
Zifeng Wang, Cao Xiao, Jimeng Sun
Abstract
Clinical trials are essential to drug development but time-consuming, costly, and prone to failure. Accurate trial outcome prediction based on historical trial data promises better trial investment decisions and more trial success. Existing trial outcome prediction models were not designed to model the relations among similar trials, capture the progression of features and designs of similar trials, or address the skewness of trial data which causes inferior performance for less common trials.
Topics & Concepts
Clinical trialOutcome (game theory)Computer scienceDrug trialMeta-analysisArtificial intelligenceMachine learningData miningMedicineInternal medicineMathematicsMathematical economicsMachine Learning in HealthcareStatistical Methods in Clinical TrialsExplainable Artificial Intelligence (XAI)