Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media for dynamic model selection and rule based data interpretation. The system receives a plurality of data sets from one or more external computing systems, each of the data sets including multiple data fields including one or more code values and data values for one or more medical tests. The system provides a plurality of medical test processing models wherein each medical test processing model includes a data interpretation rule structure for processing different types of the medical tests. The system selects a particular medical test processing model based on the one or more code values of the medical test. The system uses the selected medical test processing model to process the data values of the one or more medical tests to generate an interpreted medical test data set.

Abstract: A method of determining the risk of developing a known disease or condition or of identifying the presence of the known disease or condition in a subject includes obtaining subject data that includes results of blood tests. The blood tests include a basic metabolic panel (BMP) and a complete blood count (CBC) panel. The method further includes classifying the subject data with respect to the risk of the subject having or developing the known disease or condition by using the subject data in a machine learning classification system. The classification system includes a machine learning model previously trained on BMP and CBC data from a positive group of training subjects who received a diagnosis of the disease or condition and from a negative group of training subjects who were not diagnosed to have the disease or condition.

Abstract: A method of determining the risk of developing a known disease or condition or of identifying the presence of the known disease or condition in a subject includes obtaining subject data that includes results of blood tests. The blood tests include a basic metabolic panel (BMP) and a complete blood count (CBC) panel. The method further includes classifying the subject data with respect to the risk of the subject having or developing the known disease or condition by using the subject data in a machine learning classification system. The classification system includes a machine learning model previously trained on BMP and CBC data from a positive group of training subjects who received a diagnosis of the disease or condition and from a negative group of training subjects who were not diagnosed to have the disease or condition.