Machine learning based system for identifying and monitoring neurological disorders

A neurological disorder, diagnosis system technology, applied in the field of neurological disorder identification and monitoring system, can solve the problems of anti-epileptic drug exposure, side effect health service utilization, etc.

Pending Publication Date: 2020-06-02
萨蒂什拉奥 +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This leads to unnecessary AED exposure, side effects and health service utilization
[0029] Another challenge is monitoring the progression of neurological disorders over time

Method used

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  • Machine learning based system for identifying and monitoring neurological disorders
  • Machine learning based system for identifying and monitoring neurological disorders
  • Machine learning based system for identifying and monitoring neurological disorders

Examples

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example

[0109] The following working example provides an exemplary embodiment of the invention and is not intended to limit the scope of the invention in any way. This is a specific embodiment of a general system for diagnosing movement disorders. Such disorders include, but are not limited to: Parkinson's disease (PD), vascular PD, drug-induced PD, multiple system atrophy, progressive supranuclear palsy, corticobasal syndrome, anterior temporal lobe dementia, psychogenic tremor, Psychogenic movement disorders and normotensive hydrocephalus; ataxias, including Friedrich's ataxia, spinocerebellar ataxias 1-14, X-linked congenital ataxia, adult-onset ataxia with tocopherol deficiency ataxia-telangiectasia, and Canavan disease; Huntington's disease, acanthocytosis, benign hereditary chorea, and Lesch-Nyan syndrome; dystonias, including Oppenheim's torsade dystonia, X-linked dystonia - Parkinson disease, dopa-responsive dystonia, cervical dystonia, rapid-onset dystonia Parkinson disease,...

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Abstract

A system and methods of diagnosing and monitoring neurological disorders in a patient utilizing an artificial intelligence based system. The system may comprise a plurality of sensors, a collection oftrained machine learning based diagnostic and monitoring tools, and an output device. The plurality of sensors may collect data relevant to neurological disorders. The trained diagnostic tool will learn to use the sensor data to assign risk assessments for various neurological disorders. The trained monitoring tool will track the development of a disorder over time and may be used to recommend ormodify the administration of relevant treatments. The goal of the system is to render an accurate evaluation of the presence and severity of neurological disorders in a patient without requiring input from an expertly trained neurologist.

Description

[0001] Patent Cooperation Treaty (PCT) patent application [0002] Cross References to Related Applications [0003] This application claims priority to U.S. Provisional Patent Application No. 62573622, filed October 17, 2017, and U.S. Patent Application No. 16162711, filed October 17, 2018, which are incorporated herein by reference. technical field [0004] This application relates to a machine learning based neurological disorder identification and monitoring system. Background technique [0005] Currently, the total economic burden of neurological disorders is estimated to exceed $800 billion annually in the United States. Early detection and diagnosis of these diseases often leads to earlier treatment and lower overall cost of care over the individual's lifetime. [0006] Currently, the diagnosis of this disease requires the involvement of a physician. The U.S. is projected to have a shortfall of 90,000 to 140,000 physicians by 2025. Globally, the shortage of health...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/11
CPCA61B5/7475A61B5/1114A61B5/112A61B5/1128A61B5/4094A61B5/4803A61B5/4836A61B5/7275A61B2560/0223A61B2562/0204A61B2562/0219A61B5/7267A61B5/0015A61B5/4082G06N20/20G16H50/30G16H50/70G16H30/40G16H40/40G16H50/20G06N5/01G06N3/044G06N3/045G06N7/00G06N5/022G06N3/08A61B5/4023G06N20/00
Inventor 萨蒂什·拉奥马修·怀尔德
Owner 萨蒂什拉奥
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