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A digital health approach to early identification and outcome monitoring in autism

A digital health approach to early identification and outcome monitoring in autism
用于自闭症早期识别和结果监测的数字健康方法
批准号:
10698193
负责人:
Geraldine Dawson
金额:
$79.36万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
未结题
起止时间:
2017-09-07 至 2027-08-31
关键词:
AddressAffectAge MonthsAssessment toolAutism DiagnosisAutomated Clinical Decision SupportBehaviorBehavior assessmentBiological MarkersBlack raceCaregiversCellular PhoneChildChild BehaviorChild DevelopmentClinicalClinical TrialsCodeCollaborationsComputer Vision SystemsComputersComputing MethodologiesDetectionDevelopmentDevicesDiagnosisDisparityEarly DiagnosisEarly identificationEducationEngineeringEthnic OriginFacial ExpressionFamilyGoalsHealth Services AccessibilityHispanicHomeHumanIncomeJointsKnowledgeLatinoMachine LearningMeasuresMethodsMonitorMotor SkillsMusculoskeletal EquilibriumNamesNursery SchoolsOutcomeOutcome MeasureParent-Child RelationsParentsParticipantPatient RecruitmentsPatternPerformancePhenotypePopulationPopulation HeterogeneityPredictive ValuePredictive Value of TestsPrimary CareProcessQuestionnairesRaceResearchSamplingSchool-Age PopulationScientistScreening procedureServicesSpecificityStandardizationTabletsTestingToddlerVideo RecordingVideotapeWorkassessment applicationautism spectrum disorderautisticautistic childrenbehavior measurementbehavioral outcomebehavioral responsebiomarker discoverybrain basedchildren of colorclinical careclinical decision supportdesigndigitaldigital deliverydigital healthfollow-upgirlshealth care settingsimplementation scienceimprovedinnovationiterative designliteracymovienovelpediatricianprimary care clinicprimary care providerprogramsprototyperecruitremote administrationremote deliveryresponsescreeningsexsocial attentionstandard of caretoolusability

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ABSTRACT – Project 1 The overall goal of the Duke Autism Center of Excellence is to use a translational digital health and computational approach to address the critical need for more effective autism screening tools, objective outcome measures, and brain-based biomarkers that can be used in clinical trials with young autistic children. The goal of Project 1 is to evaluate novel digital behavioral assessment tools based on computer vision analysis and machine learning that can be implemented in real-world settings to improve the accuracy of autism screening and enable scalable, objective longitudinal monitoring of children’s behavior and development. Project 1 will recruit a large population of 16- to 30-month-old toddlers through primary care clinics to evaluate the accuracy of a remotely administered novel digital phenotyping application (app) for detecting early signs of autism. The app automatically quantifies direct observations of children’s behavior using computer vision analysis and is deployed on a smartphone or tablet. We will assess the sensitivity, specificity, negative/positive predictive values, and test-retest reliability of the digital phenotyping app for autism detection when delivered by parents at home. We will also assess the app’s usability for longitudinal outcome monitoring of autistic children at 16-30, 36, and 48 months of age by examining its convergent validity compared to standardized clinical measures. With a goal of expanding the types of behavioral measures that could be used for autism screening and outcome monitoring, we will explore the feasibility of using computer vision analysis to measure parent-child interaction from videos recorded at home. Finally, in collaboration with Project 2, we will design an automated clinical decision support for primary care providers that integrates autism screening information with actionable guidance regarding referrals for diagnosis and services and assess its perceived usability. Our long-term vision is to transform how clinical care is delivered by providing innovative solutions that address long-standing barriers in access to care.
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Novel Approaches to Infant Screening for ASD in Pediatric Primary Care
  • 批准号:
    10443752
  • 项目类别:
  • 资助金额:
    $78.1万
  • 财政年份:
    2019
  • 负责人:
    Geraldine Dawson
  • 依托单位:
Scalable Computational Platform For Active Closed-Loop Behavioral Coding in Autism Spectrum Disorder
  • 批准号:
    10440249
  • 项目类别:
  • 资助金额:
    $38.67万
  • 财政年份:
    2019
  • 负责人:
    Geraldine Dawson
  • 依托单位:
Novel Approaches to Infant Screening for ASD in Pediatric Primary Care
  • 批准号:
    10227331
  • 项目类别:
  • 资助金额:
    $78.18万
  • 财政年份:
    2019
  • 负责人:
    Geraldine Dawson
  • 依托单位:
Novel Approaches to Infant Screening for ASD in Pediatric Primary Care
  • 批准号:
    10018110
  • 项目类别:
  • 资助金额:
    $78.56万
  • 财政年份:
    2019
  • 负责人:
    Geraldine Dawson
  • 依托单位:
海外基金