An apparatus for monitoring of a patient undergoing a Magnetic Resonance Image scan, the apparatus comprising: - an input unit; - a processing unit; and - an output unit; wherein, the input unit is configured to provide the processing unit with at least one sensor data of a patient undergoing an MRI scan by an MRI scanner; wherein, the input unit is configured to provide the processing unit with at least one scan parameter of the MRI scanner for the MRI scan; wherein, the input unit is configured to provide the processing unit with at least one characteristic of the patient; wherein, the processing unit is configured to implement at least one machine learning algorithm to predict a future stress level of the patient and/or predict a future likelihood of movement of the patient, the prediction or predictions comprising utilization of the at least one sensor data of the patient, the at least one scan parameter of the MRI scanner, and the at least one characteristic of the patient, and wherein the at least one machine leaming algorithm was trained on the basis of: at least one sensor data of one or more reference patients undergoing one or more reference MRI scans by one or more reference MRI scanners; at least one scan parameter of the reference MRI scanners used for the one or more reference MRI scans; at least one characteristic of each of the reference patients; at least one stress level and/or likelihood of movement of the one or more reference patients experienced during the one or more reference MRI scans; and wherein, the output unit is configured to output information relating to the predicted future stress level of the patient and/or the predicted future likelihood of movement of the patient. - an input unit; - a processing unit; and - an output unit; wherein, the input unit is configured to provide the processing unit with at least one sensor data of a patient undergoing an MRI scan by an MRI scanner; wherein, the input unit is configured to provide the processing unit with at least one scan parameter of the MRI scanner for the MRI scan; wherein, the input unit is configured to provide the processing unit with at least one characteristic of the patient; wherein, the processing unit is configured to implement at least one machine learning algorithm to predict a future stress level of the patient and/or predict a future likelihood of movement of the patient, the prediction or predictions comprising utilization of the at least one sensor data of the patient, the at least one scan parameter of the MRI scanner, and the at least one characteristic of the patient, and wherein the at least one machine leaming algorithm was trained on the basis of: at least one sensor data of one or more reference patients undergoing one or more reference MRI scans by one or more reference MRI scanners; at least one scan parameter of the reference MRI scanners used for the one or more reference MRI scans; at least one characteristic of each of the reference patients; at least one stress level and/or likelihood of movement of the one or more reference patients experienced during the one or more reference MRI scans; and wherein, the output unit is configured to output information relating to the predicted future stress level of the patient and/or the predicted future likelihood of movement of the patient. wherein, the input unit is configured to provide the processing unit with at least one sensor data of a patient undergoing an MRI scan by an MRI scanner; wherein, the input unit is configured to provide the processing unit with at least one scan parameter of the MRI scanner for the MRI scan; wherein, the input unit is configured to provide the processing unit with at least one characteristic of the patient; wherein, the processing unit is configured to implement at least one machine learning algorithm to predict a future stress level of the patient and/or predict a future likelihood of movement of the patient, the prediction or predictions comprising utilization of the at least one sensor data of the patient, the at least one scan parameter of the MRI scanner, and the at least one characteristic of the patient, and wherein the at least one machine leaming algorithm was trained on the basis of: at least one sensor data of one or more reference patients undergoing one or more reference MRI scans by one or more reference MRI scanners; at least one scan parameter of the reference MRI scanners used for the one or more reference MRI scans; at least one characteristic of each of the reference patients; at least one stress level and/or likelihood of movement of the one or more reference patients experienced during the one or more reference MRI scans; and wherein, the output unit is configured to output information relating to the predicted future stress level of the patient and/or the predicted future likelihood of movement of the patient.