Predictive Analysis in Chiari Malformation Type I

Abstract

It has become increasingly accepted that the various facets of medicine are not deterministic. Clinicians must weigh not just a set of fixed benchmarks while determining optimal patient care but must also incorporate a growing set of health data generated by their patients. The future of personalized healthcare lies in predictive analytics that utilizes algorithmically derived probabilities to augment patient care. Such an approach has immense potential in a condition such as Chiari I malformation that is characterized by heterogeneous presentations, management options, and postsurgical outcomes. The authors review various predictors identified in relation to CM I and discuss the findings and relevance of two novel algorithms in predicting outcome after CM I surgery.