CPC G16H 10/60 (2018.01) [G06N 20/00 (2019.01); G16H 20/00 (2018.01)] | 20 Claims |
1. A computer-implemented method for generating a care and treatment plan for a patient, comprising:
(a) receiving an initial series of care records;
(b) generating a first plurality of care data groups based on the initial series of care records, each care data group comprising at least two care records from the initial series;
(c) generating a feature vector for each care data group of the first plurality of care data groups to obtain a first plurality of feature vectors;
(d) inputting each feature vector of the first plurality of feature vectors into a trained machine-learning model to determine if a care data group is to be merged into a single medical episode to identify a new series of care records, medical episodes, or a combination thereof;
(e) generating a second plurality of care data groups based on the new series, each care data group comprising at least: two care records, two medical episodes, or a care record and a medical episode;
(f) generating a feature vector for each care data group of the second plurality of care data groups to obtain a second plurality of feature vectors;
(g) inputting each feature vector of the second plurality of feature vectors into the trained machine-learning model to determine if a care data group is to be merged into a single medical episode to update the new series of care records, medical episodes, or a combination thereof;
(h) repeating steps (e)-(g) zero or more times using the new series to identify a final series of medical episodes, wherein each medical episode of the final series of medical episodes corresponds to one or more care records in the initial series of care records; and
(i) creating a patient profile for the patient, the patient profile comprising at least a subset of the final series of medical episodes; and
(j) generating the care and treatment plan for the patient based on the patient profile by:
training one or more machine-learning models using a plurality of medical episodes corresponding to patients similar to the patient; and
generating the care and treatment plan based on the trained one or more machine-learning models and one or more medical episodes in the patient profile.
|