Abstract: Various embodiments of the present disclosure provide methods, apparatus, systems, computing devices, computing entities, and/or the like for classifying unstructured data by: (i) generating probability scores of natural language classification labels for classifying unstructured data elements using an NLP-based model, (ii) generating probability scores of structured data classification labels for classifying the unstructured data elements using a classification-based model, and (iii) assigning classifications labels based on: a) the probability scores of the natural language classification labels if a distance measure difference associated with the natural language classification labels is greater than a predetermined distance, or b) a determination using an ensemble model if the distance measure difference is less than a predetermined distance.

Abstract: Various embodiments of the present disclosure provide methods, apparatus, systems, computing devices, computing entities, and/or the like for classifying unstructured data by: (i) generating probability scores of natural language classification labels for classifying unstructured data elements using an NLP-based model, (ii) generating probability scores of structured data classification labels for classifying the unstructured data elements using a classification-based model, and (iii) assigning classifications labels based on: a) the probability scores of the natural language classification labels if a distance measure difference associated with the natural language classification labels is greater than a predetermined distance, or b) a determination using an ensemble model if the distance measure difference is less than a predetermined distance.

Abstract: A method comprises: for each respective factor of a plurality of factors that affect a risk of surgical error occurring when a surgeon performs a surgery on a patient: obtaining, by a computing system, a factor value for the respective factor; and applying, by the computing system, a machine-learned weight for the respective factor to the factor value for the respective factor to determine a weighted factor value for the respective factor; determining a risk score for the surgery based on the weighted factor values for the factors, wherein the risk score is a measure of the risk of surgical error occurring during the surgery given the factor values for the plurality of factors; and generating, by the computing system, based on the risk score for the surgery, a recommendation regarding the surgery.