Digital neurology

K K Jain MD (Dr. Jain is a consultant in neurology and has no relevant financial relationships to disclose.)
Originally released March 13, 2019; expires March 13, 2022

This article includes discussion of digital neurology, applications of digital technologies in neurologic disorders, artificial intelligence, brain-computer interface, computer simulation of the brain and machine learning, digital technologies for personalized neurology, electronic patient records, neurorobotics, and the use of mobile devices in neurology. The foregoing terms may include synonyms, similar disorders, variations in usage, and abbreviations.

Overview

Digital neurology involves the use of digital technologies in clinical practice as well as in research in the neurosciences. Digital tools include mobile devices and wearable biosensors. The scope of digital neurology includes analysis of data generated via algorithms, neuroimaging, electronic medical records, artificial intelligence, neurorobotics, the use of digital biomarkers for clinical trials, and the development of personalized medicine.

Key points

 

• Digital neurology, as part of digital medicine, involves digitalization of human healthcare data; use of biosensors to track body functions; as well as processing of the vast data generated via algorithms, cloud computing, and artificial intelligence.

 

• Portable and wearable devices are being used not only for diagnosis, but also for the integration of diagnosis with therapeutics for personalized neurology.

 

• Artificial intelligence, using algorithms based on computational models of biological neural networks, is integrated in machines such as neurorobots or neuroprosthetic devices for neurorehabilitation.

 

• Electronic medical records are widely used in healthcare to improve efficacy and reduce costs, but its use in neurology has been limited by requirements of complex diagnostic data.

 

• Digital biomarkers are used in clinical trials of neurologic disorders.

Historical note and terminology

Digital medicine is defined as the use of digital tools to advance the practice of medicine to high-definition as well as individualized levels and encompasses our ability to digitize human beings using biosensors that not only track our complex physiologic systems, but also process the vast data generated via algorithms, cloud computing, and artificial intelligence (Steinhubl and Topol 2018). An important feature is the development of technological solutions to monitor, process, and integrate different data at the individual and population levels to help address the health problems and challenges faced by patients, clinicians, and healthcare systems. The scope of digital medicine is much broader and includes mobile devices, neuroimaging, electronic medical records, artificial intelligence, robotics, and personalized medicine. Digital technologies are used in pharmaceutical medicine and clinical trials. In April 2018, the U.S. Food and Drug Administration (FDA) granted approval to an artificial intelligence–based device to detect certain diabetes-related eye problems. This was the first market approval of a medical device that performs a screening test and provides a referral to a specialist without the need for a clinician to interpret the image or results. Digital neurology includes the application of all these digital tools in the neurosciences.

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