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• autoSCORE is intended for the review, monitoring and analysis of EEG recordings made by electroencephalogram (EEG) devices using scalp electrodes and to aid neurologists in the assessment of EEG. This device is intended to be used by qualified medical practitioners who will exercise professional judgment in using the information. • The spike detection component of autoSCORE is intended to mark previously acquired sections of the patient's EEG recordings that may correspond to spikes, in order to assist qualified clinical practitioners in the assessment of EEG traces. The spike detection component is intended to be used in patients at least three months old for EEGs <4 hours and at least two years old for EEGs >4 hours. The autoSCORE component has not been assessed for intracranial recordings. • autoSCORE is intended to assess the probability that previously acquired sections of EEG recordings contain abnormalities, and classifies these into pre-defined types of abnormalities, including epileptiform and non-epileptiform abnormalities. autoSCORE does not have a user interface. autoSCORE sends this information to the EEG reviewing software to indicate where markers indicating abnormality are to be placed in the EEG. autoSCORE also provides the probability that EEG recordings include abnormalities and the type of abnormalities. The user is required to review the EEG and exercise their clinical judgement to independently make a conclusion supporting or not supporting brain disease. • This device does not provide any diagnostic conclusion about the patient's condition to the user. The device is not intended to detect or classify seizures.

autoSCORE is a software only device. autoSCORE is an AI model that has been trained with standard deep learning principles using a large training dataset. The model will be locked in the field, so it cannot learn from data to which it is exposed when in use. It can only be used with a compatible electroencephalogram (EEG) reviewing software, which acquires and displays the EEG. The model has no user interface. The form of the visualization of the annotations is determined and provided by the EEG reviewing software. autoSCORE has been trained to identify and then indicate to the user sections of EEG which may include abnormalities and to provide the level of probability of the presence of an abnormality. The algorithm also provides categorization of identified areas of abnormality into the four predefined types of abnormalities, again including a probability of that predefined abnormality type. This is performed by identifying epileptiform abnormalities/spikes (Focal epileptiform and generalised epileptiform) as well identifying non-epileptiform abnormalities (Focal non-epileptiform and Diffuse Non-Epileptiform). This data is then provided by the algorithm to the EEG reviewing software, for it to display as part of the EEG output for the clinician to review. autoSCORE does not provide any diagnostic conclusion about the patient's condition nor treatment options to the user, and does not replace visual assessment of the EEG by the user. This device is intended to be used by qualified medical practitioners who will exercise professional judgment in using the information.

1. autoSCORE is intended for the review, monitoring and analysis of EEG recordings made by electroencephalogram (EEG) devices using scalp electrodes and to aid neurologists in the assessment of EEG. This device is intended to be used by qualified medical practitioners who will exercise professional judgment in using the information. 2. The spike detection component of autoSCORE is intended to mark previously acquired sections of the patient's EEG recordings that may correspond to spikes, in order to assist qualified clinical practitioners in the assessment of EEG traces. The spike detection component is intended to be used in patients at least three months old. The autoSCORE component has not been assessed for intracranial recordings. 3. autoSCORE is intended to assess the probability that previously acquired sections of EEG recordings contain abnormalities, and classifies these into pre-defined types of abnormalities, including epileptiform abnormalities. autoSCORE does not have a user interface. autoSCORE sends this information to the EEG reviewing software to indicate where markers indicating abnormality are to be placed in the EEG. autoSCORE also provides the probability that EEG recordings include abnormalities and the type of abnormalities. The user is required to review the EEG and exercise their clinical judgendently make a conclusion supporting or not supporting brain disease. 4. This device does not provide any diagnostic conclusion about the patient's condition to the user. The device is not intended to detect or classify seizures.

autoSCORE is a software-only decision support product intended to be used with compatible electroencephalography (EEG) review software. It is intended to assist the user when reviewing EEG recordings, by assessing the probability that previously acquired sections of EEG recordings contain abnormalities, and classifying these into pre-defined types of abnormality. autoSCORE sends this information to the EEG software to indicate where markers indicating abnormality are to be placed in the EEG. autoSCORE uses an algorithm that has been trained with standard deep learning principles using a large training dataset. autoSCORE also provides an overview of the probability that EEG recordings and sections of EEG recordings include abnormalities, and which type(s) of abnormality they include. This is performed by identifying spikes of epileptiform abnormalities (Focal epileptiform and Generalized epileptiform) as well identifying non-epileptiform abnormalities (Focal Nonepileptiform and Diffuse Non-epileptiform). The user is required to review the EEG and exercise their clinical judgement to independently make a conclusion supporting or not supporting brain disease. autoSCORE cannot detect or classify seizures. The recorded EEG activity is not altered by the information provided by autoSCORE. autoSCORE is not intended to provide information for diagnosis but to assist clinical workflow when using the EEG software.