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US Patent 9536052 Clinical predictive and monitoring system and method

Patent 9536052 was granted and assigned to Parkland Center For Clinical Innovation on January, 2017 by the United States Patent and Trademark Office.

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Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent
1

Patent attributes

Current Assignee
Parkland Center For Clinical Innovation
Parkland Center For Clinical Innovation
1
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
1
Patent Number
95360521
Patent Inventor Names
Ying Ma1
Rubendran Amarasingham1
Sambamurthy Nalla1
Timothy S. Swanson1
Yu Qian1
Christopher A. Clark1
George R. Oliver1
Kimberly P. Gerra1
Date of Patent
January 3, 2017
1
Patent Application Number
136139801
Date Filed
September 13, 2012
1
Patent Citations Received
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US Patent 12106842 Systems, methods, and media for automated dietary management in healthcare facilities
2
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US Patent 11911187 Monitoring a subject
3
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US Patent 11915834 Efficient volume matching of patients and providers
4
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US Patent 11923086 Senior living engagement and care support platforms
5
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US Patent 11923087 Senior living engagement and care support platforms
6
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US Patent 11935651 Alert systems for senior living engagement and care support platforms
7
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US Patent 11967432 Method and system for remotely monitoring the physical and psychological state of an application user using altitude and/or motion data and one or more machine learning models
8
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US Patent 11996194 Senior living engagement and care support platforms
9
...
Patent Primary Examiner
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Stanley K. Hill
1
Patent abstract

A clinical predictive and monitoring system comprising a data store operable to receive and store data associated with a plurality of patients selected from medical and health data; and a number of social, behavioral, lifestyle, and economic data; at least one predictive model to identify at least one high-risk patient associated with at least one medical condition; a risk logic module operable to apply the at least one predictive model to the patient data to determine at least one risk score associated the at least one medical condition and identify at least one high-risk patient; a data presentation module operable to present notification and information to an intervention coordination team about the identified at least one high-risk patient; and an artificial intelligence tuning module adapted to automatically adjust parameters in the predictive model in response to trends in the patient data.

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