Abstract: Disclosed are systems and methods for classifying brain lesions based on single point in time imaging, methods for training a machine learning model for classifying brain lesions, and a method of predicting formation of brain lesions based on single point in time imaging. A method of classifying brain lesions based on single point in time imaging can include; accessing patient image data from a single point in time; providing the patient image data as an input to a brain lesion classification model; generating a classification for each of one or more lesions identified in the patient image data; and providing the classification for each of the one or more lesions for display on one or more display devices; wherein the brain lesion classification model is trained using subject image data for a plurality of subjects, the subject image data being captured at two or more points in time.

Abstract: The present disclosure relates to the field of diagnostics, specifically, to a method of identifying progressing multiple sclerosis (MS) in a subject. At least one performance parameter is determined from a dataset of activity measurements obtained from the subject using a mobile device, and the performance parameter is compared to a reference, whereby a subject with progressing MS will be identified. Also disclosed is a method of recommending an anti-CD20 antibody therapy against MS that includes the steps just mentioned and the further step of recommending the anti-CD20 antibody therapy if the subject suffers from progressing MS. Also disclosed is a mobile device having a processor, at least one sensor and a database as well as software which is tangibly embedded to the device and, when running on said device, carries out the method of this disclosure as well as the use of such a device for identifying a subject suffering from progressing MS.

Abstract: A method for automatically assessing information processing speed in a test subject is disclosed. In the inventive method, a first qualimetric activity parameter for sensorial transmission, cognition and motoric output activity is determined and a second qualimetric activity parameter for sensorial transmission and motoric output activity is determined. A third qualimetric activity parameter for cognition is determined by comparing the first and the second qualimetric activity parameters to each other, and the information processing speed in the test subject is assessed based on the first, second and third qualimetric activity parameters. The information processing speed can be determined by comparing the determined qualimetric activity parameters to a reference and the subject's cognitive impairment can then be determined from the processing speed. The inventive method can be computer implemented. A mobile device or system for carrying out the disclosed methods is also disclosed.

Abstract: Disclosed is a method for assessing a cognition and movement disease or disorder in a subject. In the method, a qualimetric activity parameter for cognition and/or fine motoric activity measurements is determined from a dataset of measurements obtained from the subject using a mobile device. The qualimetric activity parameter is compared to a reference and the disease or disorder is thereby assessed. A method identifying whether a subject will benefit from a therapy for a cognition and movement disease or disorder is also disclosed. The method can be carried out with a mobile device having a processor, a sensor and a database as well as software that carries out the method. Also disclosed is a system having a mobile device with a sensor and a remote device having a processor and a database and software that carries out the method for assessing a cognition and movement disease or disorder.

Abstract: The present disclosure relates to the field of diagnostics, specifically, to a method of identifying progressing multiple sclerosis (MS) in a subject. At least one performance parameter is determined from a dataset of activity measurements obtained from the subject using a mobile device, and the performance parameter is compared to a reference, whereby a subject with progressing MS will be identified. Also disclosed is a method of recommending an anti-CD20 antibody therapy against MS that includes the steps just mentioned and the further step of recommending the anti-CD20 antibody therapy if the subject suffers from progressing MS. Also disclosed is a mobile device having a processor, at least one sensor and a database as well as software which is tangibly embedded to the device and, when running on said device, carries out the method of this disclosure as well as the use of such a device for identifying a subject suffering from progressing MS.

Abstract: A method for assessing a cognition and movement disease or disorder in a subject suspected to suffer therefrom. A cognition and/or fine motoric activity parameter is determined from a dataset of activity measurements obtained from the subject using a mobile device. The determined activity parameter is compared to a reference, and the cognition and movement disease or disorder is assessed. Also disclosed is a method for identifying whether a subject will benefit from a therapy for a cognition and movement disease or disorder. The steps just described are performed along with the step of identifying the subject as one who benefits from the therapy if the cognition and movement disease or disorder is assessed. Also disclosed is a mobile device comprising a processor, at least one sensor, a database and software which is tangibly embedded in said device and, when running on said device, carries out the disclosed methods.