Systems and methods to identify a subgroup of ADHD at higher risk for complicating conditions
First Claim
1. A system for identifying a subgroup of attention deficit hyperactivity disorder (ADHD) patients at higher risk for complicating conditions, the system comprising:
- a data collection module operable to;
receive, from a user or clinician, evaluation data associated with a plurality of patients identified with ADHD as a primary diagnosis; and
obtain EEG data for each of the plurality of patients;
a clinical/diagnostic module operable to;
based at least in part on the EEG data, determine an indicator of ADHD, wherein the indicator supports a positive or negative ADHD evaluation; and
a subgroup identification module operable to;
correlate the indicator with the user'"'"'s or clinician'"'"'s evaluation data; and
based at least in part on the correlation, determine at least one subgroup of the plurality of patients, wherein the correlation provides positive support for diagnosis of ADHD or provides support for further testing for complicating conditions before proceeding with diagnosis of ADHD in at least one patient within the at least one subgroup.
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Accused Products
Abstract
This invention is directed to embodiments of systems and methods to identify a subgroup of ADHD at higher risk for complicating conditions that, for example, may be of concern to an ADHD evaluation, may account for attention and behavior symptoms, and may lead a clinician to exclusion of ADHD from primary diagnosis. In one embodiment, a method for identifying a subgroup of attention deficit hyperactivity disorder (ADHD) patients at higher risk for complicating conditions is provided. The method can include receiving, from a user or clinician, evaluation data associated with a plurality of patients identified with ADHD as a primary diagnosis; obtaining EEG data for each of the plurality of patients; determining, based at least in part on the EEG data, an indicator of ADHD, wherein the indicator supports a positive or negative ADHD evaluation; correlating the indicator with a user'"'"'s or clinician'"'"'s evaluation data; and based at least in part on the correlation, determining at least one subgroup of the plurality of patients, wherein the correlation provides positive support for diagnosis of ADHD or provides support for further testing for complicating conditions before proceeding with diagnosis of ADHD in at least one patient within the at least one subgroup.
35 Citations
20 Claims
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1. A system for identifying a subgroup of attention deficit hyperactivity disorder (ADHD) patients at higher risk for complicating conditions, the system comprising:
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a data collection module operable to; receive, from a user or clinician, evaluation data associated with a plurality of patients identified with ADHD as a primary diagnosis; and obtain EEG data for each of the plurality of patients; a clinical/diagnostic module operable to; based at least in part on the EEG data, determine an indicator of ADHD, wherein the indicator supports a positive or negative ADHD evaluation; and a subgroup identification module operable to; correlate the indicator with the user'"'"'s or clinician'"'"'s evaluation data; and based at least in part on the correlation, determine at least one subgroup of the plurality of patients, wherein the correlation provides positive support for diagnosis of ADHD or provides support for further testing for complicating conditions before proceeding with diagnosis of ADHD in at least one patient within the at least one subgroup. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A computer program product, comprising a computer readable medium having computer readable code adapted to be executed to implement a method for identifying a subgroup of attention deficit hyperactivity disorder (ADHD) patients at higher risk for complicating conditions, the method comprising:
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receiving, from a user or clinician, evaluation data associated with a plurality of patients identified with ADHD as a primary diagnosis; obtaining, via the data collection module, EEG data for each of the plurality of patients; based at least in part on the EEG data, determining an indicator of ADHD via the clinical/diagnostic module, wherein the indicator supports a positive or negative ADHD evaluation; correlating the indicator with the user'"'"'s or clinician'"'"'s evaluation data; and based at least in part on the correlation, determining, via the subgroup identification module, at least one subgroup of the plurality of patients, wherein the correlation provides positive support for diagnosis of ADHD or provides support of further testing for complicating conditions before proceeding with diagnosis of ADHD in at least one patient within the at least one subgroup. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A computer-implemented method for identifying a subgroup of attention deficit hyperactivity disorder (ADHD) patients at risk for complicating conditions, the method comprising:
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using a data collection module, receiving, from a user or clinician, evaluation data associated with a plurality of patients identified with ADHD as a primary diagnosis; and obtaining EEG data for each of the plurality of patients; using a clinical/diagnostic module, based at least in part on the EEG data, determining an indicator of ADHD, wherein the indicator supports a positive or negative ADHD evaluation; and using a subgroup identification module, correlating the indicator with the user'"'"'s or clinician'"'"'s evaluation data; and based at least in part on the correlation, determining at least one subgroup of the plurality of patients, wherein the correlation provides positive support for diagnosis of ADHD or provides support for further testing for complicating conditions before proceeding with diagnosis of ADHD in at least one patient within the at least one subgroup. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification