Systems and methods are described herein for determining that a patient has indications mild cognitive impairment (MCI) or early stage Alzheimer's disease (AD). Microperimetry is used to assess the functional integrity of the patient's retina. Optical Coherence Tomography is used to assess the structural integrity of the patient's retina. Reductions in the size and function of the patient's retina indicate that the patient may have MCI or early stage AD.

The present invention relates to a method for predicting neurodegenerative decline and/or its severity for a patient, especially of cognitive impairment (CI). Strokes and Parkinson's disease are frequently associated with occurrence of long-term cognitive impairment or dementia with still incompletely resolved mechanisms. The discovery of diagnostic and predictive biomarkers thus remains a major challenge. The method of the invention uses radiomics corresponding to texture features extracted from a plurality of previously-acquired medical brain images and correlated with previously-acquired clinical and/or biological data. A classifier is trained beforehand for learning these radiomics, and then operated on radiomics computed from at least one brain image of a patient to generate a score representative of its risks of neurodegenerative decline. By applying this method on a cohort of 160 MCI and non-MCI patients, the inventors show that MCI patients could be early predicted with a mean accuracy of 88%. In the same way, the method was able to discriminate very early stages of cognitive decline in a Parkinson's disease population of 100 patients.

A method, computer program product, and computing system for monitoring one or more environmental variables concerning a client electronic device configured to administer an alertness test to a user. A disrupter is selected for inclusion within the alertness test based, at least in part, upon the one or more environmental variables concerning the client electronic device. The alertness test is administered to the user.

A system and method for diagnosis and therapeutic treatment of patients with neurological disease from a plurality of sensors, and in particular, to such a system, method and apparatus for analyzing data from a plurality of sensors with an AI (artificial intelligence) algorithm.

Fixational eye movement may be analyzed to determine one or more characteristics thereof. Exemplary characteristics include measurements of microsaccade and drift measurement. These measurements may be correlated to a value for a diagnostic indicator for a neurological disorder or disease. These correlations may be used to diagnose, monitor, and prognosticate neurological disorders without administration of traditionally used neurological function tests or analysis of biological samples by which the diagnostic indicators are typically determined.

The present invention is adapted for recognition technology improvement, which provides a memory identification and recovery method based on recognition, including: S1. collecting the data information from the scene of activity through a recognition device; S2. conducting salient feature extraction to the data information collected from the scene and generating feature marks; S3. building mapping relations between the generated feature marks and the extracted data information, automatically generating memory information in the database, and storing the information in the database; S4. inputting related data information for searching; S5. selecting a corresponding method to search the generated memory information in the database based on the input data information; S6. determining if there is related data information in the memory data. The method can helps to enhance memory of the user, recover memory after forget it, recover effectively through recognition technology, improve memory, and retrieve memory quickly after memory loss, which is convenient and efficient.

In various aspects and embodiments provided are compositions and methods for identifying patients in need of improving cognition and/or treating a neurodegenerative disease in a patient and treating such patient.

There are provided an estimation system, an estimation program and an estimation method through which voice spoken by a subject is estimated, a disease from which the subject is suffering is distinguished and estimated, aggravation of the disease is prevented, and patients are able to receive appropriate treatment based on accurate distinguishing of the disease.

An exemplary system, method and computer-accessible medium for determining a dopamine function of a patient(s) can include, for example, receiving imaging information of a brain of the patient(s), determining a Neuromelanin (NM) concentration of the patient(s) based on the imaging information, and determining the dopamine function based on the NM concentration. The NM concentration can be determined using a voxel-wise analysis procedure. The voxel-wise analysis procedure can be used to determine a topographical pattern(s) within a substantia nigra (SN) of the brain of the patient(s). The topographical pattern(s) can include a pattern(s) of cell loss in the SN. The NM concentration can be based on a NM loss in the brain of the patient(s).

The present specification describes a system for diagnosing or screening one or more pathologies in a patient. The system includes a headset with at least one microphone or accelerometer to passively receive vibrations generated by the cerebral vasculature of the patient's brain, computing devices coupled with the headset for processing the received vibrations to obtain a unique signal, and a signal analyzer to analyze the signal in order to determine if the data includes patterns uniquely indicative of at least one of tension headaches, migraines, depression, dementia, Alzheimer's disease, epilepsy, Parkinson's disease, autism, cerebral vasospasm and meningitis.