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US Patent 11776677 Computer vision-based analysis of provider data

Patent 11776677 was granted and assigned to PEARL on October, 2023 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent

Patent attributes

Patent Applicant
PEARL
PEARL
Current Assignee
PEARL
PEARL
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
11776677
Patent Inventor Names
Cambron Neil Carter
Hamza Surti
Ophir Tanz
Joshua Alexander Tabak
Date of Patent
October 3, 2023
Patent Application Number
17569370
Date Filed
January 5, 2022
Patent Citations
‌
US Patent 7602965 Object detection using cross-section analysis
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US Patent 7269278 Extracting shape information contained in cell images
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US Patent 7421398 System and method for implementing healthcare fraud countermeasures
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US Patent 7472275 System and method of electronic signature verification
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US Patent 10201318 Periodontal disease diagnosis supporting device, periodontal disease diagnosis supporting system, periodontal disease diagnosis supporting program, and periodontal disease diagnosis supporting method
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US Patent 10410363 Jaw surface based registration
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US Patent 10426351 Systems and methods for spatial positioning of diagnostic and or treatment probe based on surface profile detection
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US Patent 10722191 Digital X-ray diagnosis and evaluation of dental disease
...
Patent Citations Received
‌
US Patent 11948094 Selecting attributes by progressive sampling to generate digital predictive models
0
Patent Primary Examiner
‌
Dilek B Cobanoglu
CPC Code
‌
G06Q 10/10
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A61C 8/00
Patent abstract

Systems and methods are described for utilizing machine learning techniques to analyze data associated with one or more dental practices to identify missed treatment opportunities, future treatment opportunities, or provider performance metrics. The treatment opportunities or performance metrics may be determined or identified based at least in part on a comparison of patient data, such as data stored in association with a dental office's practice management system, with the output of one or more machine learning models' processing of associated radiograph images of the dental office's patients. The one or more machine learning models may include models that identify, from image data of a radiograph, a dental condition depicted in the radiograph, which may be mapped by a computer system to a corresponding dental treatment recommended for the identified dental condition.

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