Artificial intelligence (AI) has been making significant strides in the field of telemedicine, particularly in vascular neurology, neuro-ophthalmology, neuro-otology, and epilepsy. The integration of AI into these branches of neurology could allow for the development of more accessible and efficient patient care, as well as advancements in research and innovations in treatment.
Impacts of AI include machine learning algorithms to analyze medical imagery e.g. detecting vascular events on retinal imaging, and detecting and predicting ocular diseases such as optic neuritis, glaucoma, and diabetic retinopathy. A range of application types are being actively explored, from hospital workflow, bedside tools, large scale data analysis, remote monitoring, longitudinal follow up, stratification and forecasting.
These applications may permit more efficient and accurate diagnosis of such conditions and enable faster interventions
This special issue will bring together the most recent advances in these related fields. The use of AI and telemedicine is certain to rise in coming years, across vascular neurology, neuro-ophthalmology, neuro-otology, and epilepsy. In other medical specialties AI has provided numerous solutions that make health care more effective, efficient and accessible. Although AI is still in its early stages of development, it holds enormous potential, and the collaborative effort between machine and human intelligence remains a promising future for neurology in telemedicine. Communicating shared expertise in this emerging area across fields will be crucial to effective development and rollout. The literature on AI methods is scattered across conference proceedings, non-peer-reviewed preprints, and smaller specialist clinical journals. This makes it difficult for clinicians to access and synthesise information pertaining to their clinical practice.
This issue will allow sharing of techniques and translational approaches across neurological subspecialties, at a critical time when these approaches are rapidly expanding.
A range of topics within stroke neurology, epilepsy, neuro-otology and neuro-opthalmology are encouraged. These subspecialties may specifically benefit greatly from the fusion of AI and telemedicine due to their need for rapid remote monitoring, and manifest clinical signs that may be detectable digitally. Papers may range from very initial demonstration of an AI technology in humans, through to assessment of their efficacy in clinical practice.
For instance, domains of interest may include vestibular tests, falls detection, EEG or ECG analysis in epilepsy, neuroimaging applications in stroke, the role of AI chatbots in telemedicine or education, ocular biomarkers or analysis of data from wearables. We anticipate studies of a range of applications from early diagnosis, stratification, increasing reach, treatment monitoring and dose titration.
Artificial intelligence (AI) has been making significant strides in the field of telemedicine, particularly in vascular neurology, neuro-ophthalmology, neuro-otology, and epilepsy. The integration of AI into these branches of neurology could allow for the development of more accessible and efficient patient care, as well as advancements in research and innovations in treatment.
Impacts of AI include machine learning algorithms to analyze medical imagery e.g. detecting vascular events on retinal imaging, and detecting and predicting ocular diseases such as optic neuritis, glaucoma, and diabetic retinopathy. A range of application types are being actively explored, from hospital workflow, bedside tools, large scale data analysis, remote monitoring, longitudinal follow up, stratification and forecasting.
These applications may permit more efficient and accurate diagnosis of such conditions and enable faster interventions
This special issue will bring together the most recent advances in these related fields. The use of AI and telemedicine is certain to rise in coming years, across vascular neurology, neuro-ophthalmology, neuro-otology, and epilepsy. In other medical specialties AI has provided numerous solutions that make health care more effective, efficient and accessible. Although AI is still in its early stages of development, it holds enormous potential, and the collaborative effort between machine and human intelligence remains a promising future for neurology in telemedicine. Communicating shared expertise in this emerging area across fields will be crucial to effective development and rollout. The literature on AI methods is scattered across conference proceedings, non-peer-reviewed preprints, and smaller specialist clinical journals. This makes it difficult for clinicians to access and synthesise information pertaining to their clinical practice.
This issue will allow sharing of techniques and translational approaches across neurological subspecialties, at a critical time when these approaches are rapidly expanding.
A range of topics within stroke neurology, epilepsy, neuro-otology and neuro-opthalmology are encouraged. These subspecialties may specifically benefit greatly from the fusion of AI and telemedicine due to their need for rapid remote monitoring, and manifest clinical signs that may be detectable digitally. Papers may range from very initial demonstration of an AI technology in humans, through to assessment of their efficacy in clinical practice.
For instance, domains of interest may include vestibular tests, falls detection, EEG or ECG analysis in epilepsy, neuroimaging applications in stroke, the role of AI chatbots in telemedicine or education, ocular biomarkers or analysis of data from wearables. We anticipate studies of a range of applications from early diagnosis, stratification, increasing reach, treatment monitoring and dose titration.