Computing system that generates patient-specific outcome predictions

A method executed by a processor of a computing system, comprising:

• receiving clinical data for a patient that is to undergo a treatment for a medical problem and a pre-treatment score value for the patient that is indicative of a condition of the patient prior to the patient undergoing the treatment;
• providing values in the clinical data and the pre-treatment score value as input to a computer-implemented model, wherein the computer-implemented model has been trained using training data comprising values for features associated with a plurality of patients that have undergone the treatment, wherein a feature in the features comprises a difference between a post-treatment score and a pre-treatment score for the treatment, wherein the computer-implemented model outputs, based upon the values in the clinical data and the pre-treatment score value for the patient, a predicted difference value that is indicative of a predicted change in the condition of the patient from a first point in time to a second point in time, the first point in time occurring prior to the patient undergoing the treatment, the second point in time occurring subsequent to the patient undergoing the treatment;
• and
• based upon the pre-treatment score value for the patient and the predicted difference value, generating a predicted post-treatment score value for the patient, wherein an indication of the predicted post-treatment score value for the patient is presented on a display of a computing device.

A non-transitory computer-readable medium comprising instructions that, when executed by a processor of a server computing device, cause the processor to perform acts comprising:

• receiving, from a client computing device, clinical data for a patient that has undergone a treatment for a medical problem and a score value for the patient that has been mostly reported, the score value being indicative of a condition of the patient at a first point in time after undergoing the treatment;
• providing values in the clinical data and the score value as input to a computer-implemented model, wherein the computer-implemented model has been trained using training data comprising values for features associated with a plurality of patients that have undergone the treatment, wherein the features include a transformed score feature, wherein values for the transformed score features have been generated by applying a transformation on values for a score feature, wherein the values for the transformed score feature have a normal distribution, wherein the computer-implemented model outputs, based upon the values in the clinical data and the score value for the patient, a predicted score value corresponding to the transformed score feature that is indicative of a condition of at a second point in time, the second point in time occurring subsequent to the first point in time;
• and
• transmitting the predicted score value for the patient to the client computing device, wherein the predicted score value for the patient is presented on a display of the client computing device.