Cirrhosis Forecasting In Human Subjects

A method for use by a system for training a cirrhosis forecast model, the system including a computing platform having a hardware processor and a memory storing a software code for training the cirrhosis forecast model, the method comprising:

• receiving, using the hardware processor, a medical data for each of a plurality of human subjects;
• assigning, using the hardware processor, a subset of the human subjects as a training group for the cirrhosis forecast model;
• identifying, using the hardware processor, a plurality of cirrhosis predictive parameters from the medical data for the training group;
• generating, using the hardware processor, a cirrhosis forecast model including a weighted combination of the cirrhosis predictive parameters;
• producing, using the hardware processor and the cirrhosis forecast model, a cirrhosis prediction for at least one of the human subjects omitted from the training group;
• determining, using the hardware processor, an accuracy of the cirrhosis prediction;
• and
• adapting, using the hardware processor, the cirrhosis forecast model based on the accuracy of the cirrhosis prediction.

A computer-readable non-transitory medium having stored thereon instructions, which when executed by a hardware processor, perform a method comprising:

• receiving a medical data for each of a plurality of human subjects;
• assigning a subset of the human subjects as a training group for the cirrhosis forecast model;
• identifying a plurality of cirrhosis predictive parameters from the medical data for the training group;
• generating a cirrhosis forecast model including a weighted combination of the cirrhosis predictive parameters;
• producing, using the cirrhosis forecast model, a cirrhosis prediction for at least one of the human subjects omitted from the training group;
• determining an accuracy of the cirrhosis prediction;
• and
• adapting the cirrhosis forecast model based on the accuracy of the cirrhosis prediction.