grant

Characterizing gastrointestinal disorder trajectories for autistic sub-groups: Machine learning prediction of risk profiles and response to treatment

Organization UNIVERSITY OF SOUTHERN CALIFORNIALocation Los Angeles, UNITED STATESPosted 1 Aug 2024Deadline 30 Apr 2029
NIHUS FederalResearch GrantFY20260-11 years old1 year of age1 year oldASDASD communityAccident and Emergency departmentAddressAdvocacyAgeAge of OnsetAlternative HealthAutismAutistic DisorderBehavioralBehavioral SymptomsCare GiversCaregiversCaringChildChild YouthChildren (0-21)Children's HospitalClinicalClinical DataClinical TreatmentCodeCoding SystemCollaborationsDataData CollectionData SetDiagnosisDiagnosticDietED careER careEarly Infantile AutismElectronic Health RecordEmergency CareEmergency DepartmentEmergency Department careEmergency Room careEmergency health careEmergency medical careEmergency roomFamilyFutureGastrointestinal DiseasesHealthHealth Care UtilizationHealth Services EvaluationHealth Services ResearchInfantile AutismInterventionInterviewKanner's SyndromeKnowledgeLabelLifeLived experienceLived experiencesLos AngelesMachine LearningMeasuresMedical Care ResearchMental HealthMental HygieneMethodsNatural Language ProcessingNon-Prescription DrugsNonprescription DrugsOTC DrugsOver-the-Counter DrugsParentsPatent MedicinesPediatric HospitalsPopulationPredicting RiskPredictive FactorPrevalenceProceduresPsychological HealthQOLQuality of lifeReportingResearchResearch MethodologyResearch MethodsReview LiteratureRiskRisk AssessmentSleepSpecialtySubgroupSymptomsTimeWorkYouthYouth 10-21adolescent with ASDadolescent with autismadolescent with autism spectrum disorderadolescents on the autism spectrumadult with ASDadult with autismadult with autism spectrum disorderadults on the autism spectrumadults on the spectrumage 1age 1 yearaged 1 yearaged one yearagesanalyzing longitudinalautism communityautism spectral disorderautism spectrum disorderautism spectrum disorder communityautisticautistic adolescentautistic adultautistic childrenautistic individualsautistic peopleautistic spectrum disorderautistic youthchildren on the autism spectrumchildren with ASDchildren with autismchildren with autism spectrum disorderclinical interventionclinical therapycohortcommunity advisory boardcommunity advisory committeecommunity advisory paneldietselectronic health care recordelectronic health medical recordelectronic health plan recordelectronic health registryelectronic medical health recordexperienceforecasting riskgastrointestinalgastrointestinal disordergastrointestinal symptomhealth care service usehealth care service utilizationhigh riskimprovedindexingindividuals on the autism spectrumindividuals on the spectrumindividuals with ASDindividuals with autismindividuals with autism spectrum disorderinvestigate longitudinalkidslife spanlifespanlongitudinal analysislongitudinal investigationlongitudinal researchmachine based learningmachine learning based prediction modelmachine learning based predictive modelmachine learning predictionmachine learning prediction modelmedical specialtiesnatural language understandingone year of ageone year oldparentpeople on the autism spectrumpeople with ASDpeople with autismpeople with autism spectrum disorderperson centeredpersonalization of treatmentpersonalized medicinepersonalized therapypersonalized treatmentphysical conditioningphysical healthpredict responsivenesspredict riskpredict riskspredicted riskpredicted riskspredicting responsepredicting riskspredictive riskpredicts riskresearch and methodsresponseresponse to therapyresponse to treatmentrisk predictionrisk prediction algorithmrisk prediction modelrisk predictionsservices researchsexsocialstandard of carestructured datastudy longitudinalsurvey longitudinaltherapeutic responsetherapy responsetreatment responsetreatment responsivenesstrial regimentrial treatmentunstructured datayoungsteryouth ageyouth on the autism spectrumyouth with ASDyouth with autismyouth with autism spectrum disorder
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Gastrointestinal (GI) problems are one of the most common concerns reported by families of autistic children and youth and can have significant lifelong impacts on health, quality of life, and participation. Existing research, however, primarily relies on parent report and is cross-sectional, leaving a gap in our understanding of GI trajectories,…

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Characterizing gastrointestinal disorder trajectories for autistic sub-groups: Machine learning prediction of risk profi | Dev Procure