Computer implemented method for adaptive physiology-based monitoring of a subject

A computer-implemented method for providing physiological status monitoring, the method comprising:

• receiving subject data comprising physiological sensor data of a subject;
• and adapting a trained machine learning model for monitoring a physiological status,
• wherein the trained machine learning model is configured to determine the physiological status of the subject based on the physiological sensor data, wherein the trained machine learning model has a plurality of fixed weights and a plurality of variable weights;
• wherein adapting the trained machine learning model comprises:
• generating a first re-trained machine learning model by adapting the trained machine learning model by maintaining values of the plurality of fixed weights, and changing values of a first number of the plurality of variable weights;
• determining a level of agreement between the trained machine learning model and the first re-trained machine learning model, wherein the level of agreement is indicative of a difference between the values of the first number of the plurality of variable weights of the trained machine learning model and the values of the first number of the first re-trained machine learning model;
• based on the level of agreement, generating a second re-trained machine learning model by adapting the trained machine learning model by maintaining the values of the plurality of fixed weights, and changing values of a second number of the plurality of variable weights,
• wherein the second number is different from the first number and is smaller than the first number when the level of agreement satisfies a threshold condition indicating overfitting.