METHODS AND SYSTEMS FOR CALCULATING AND USING STATISTICAL MODELS TO PREDICT MEDICAL EVENTS

摘要

Systems and methods for generalized precursor pattern discovery that work with a wide range of biomedical signals and applications to detect a wide range of medical events are disclosed. In some embodiments, the methods and systems do not require domain-specific knowledge or significant reconfiguration based on the medical event being analyzed, hence it is also possible to discover patterns previously unknown to experts. In some embodiments, to build precursor pattern detection models, the system obtains annotated monitoring data. Positive and negative segments are extracted from the annotated monitoring data, and are preprocessed. Features are extracted from the preprocessed segments, and selected features are chosen from the extracted features. The selected features are classified to create the precursor pattern detection model The precursor pattern detection model may then be used in real time to detect occurrences of the medical event of interest.