[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100630955":3},{"organization":4,"armGroups":7,"interventions":8,"overallOfficials":7,"centralContacts":13,"locations":19,"responsibleParty":34,"collaborators":7,"id":37,"slug":38,"hasResults":39,"nctId":40,"briefTitle":41,"officialTitle":42,"acronym":7,"eligibilityCriteria":43,"healthyVolunteers":39,"sex":44,"minAge":45,"maxAge":46,"enrollmentInfo":47,"targetDuration":50,"studyType":51,"phases":7,"briefSummary":52,"conditions":53,"keywords":7,"overallStatus":55,"whyStopped":7,"lastUpdateSubmitDate":56,"lastUpdatePostDateStruct":57,"startDateStruct":60,"completionDateStruct":62,"leadSponsor":64,"locationsCount":65},{"fullName":5,"class":6},"Khon Kaen University","OTHER",null,[9],{"type":10,"name":11,"description":12,"armGroupLabels":7,"otherNames":7},"DIAGNOSTIC_TEST","No additional drugs(control Group)","This study is distinct from other clinical studies in that it does not involve any therapeutic intervention or modification of standard patient care. Instead, it evaluates a non-invasive, image-based measurement system that combines smartphone photography, a color calibration card, and artificial intelligence to quantify erythema in psoriasis lesions. Unlike conventional approaches that rely on subjective physician scoring or require specialized and costly equipment, this intervention is designed to be low-cost, accessible, and applicable in real-world settings, including patient self-monitoring at home.",[14],{"name":15,"role":16,"phone":17,"phoneExt":7,"email":18},"Suteeraporn Chaowattanapanit","CONTACT","+66891879719","csuteeraporn@yahoo.com",[20],{"facility":5,"status":7,"city":21,"state":22,"zip":23,"country":24,"countryCode":25,"cosmosGeoPoint":26,"geoPoint":31,"contacts":32},"Khon Kaen","Changwat Khon Kaen","40002","Thailand","TH",{"type":27,"coordinates":28},"Point",[29,30],102.833,16.44671,{"lat":30,"lon":29},[33],{"name":15,"role":16,"phone":17,"phoneExt":7,"email":18},{"type":35,"investigatorFullName":15,"investigatorTitle":36,"investigatorAffiliation":5,"oldNameTitle":7,"oldOrganization":7},"PRINCIPAL_INVESTIGATOR","Associate Professor","100630955","an-ai-based-erythema-measurement-system-for-psoriasis-lesions-100630955",false,"NCT07494396","An AI-Based Erythema Measurement System for Psoriasis Lesions","Development and Validation of an AI-Based Erythema Measurement System for Psoriasis Lesions Using Smartphone Imaging With Color Card Compared to Standard Color Calibration Device","Inclusion Criteria:\n\n* Adults aged ≥18 years\n* Diagnosed with psoriasis by a dermatologist\n* Presence of at least five clearly photographable lesions\n* Willing and able to take photographs using a smartphone with both a standard color calibration card and a study-specific color card at home weekly, and submit images via Line or email\n* Willing to have clinical photographs taken at baseline and at a follow-up visit\n* Provides written informed consent to participate in the study\n\nExclusion Criteria:\n\n* Presence of skin infection or other lesions that may interfere with color assessment (e.g., tattoos)\n* Use of self-tanning products or substances that alter skin color\n* Inability to perform photography or comply with study procedures","ALL","18 Years","100 Years",{"count":48,"type":49},50,"ESTIMATED","12 Weeks","OBSERVATIONAL","Psoriasis is a common chronic inflammatory skin disease. Disease severity is commonly assessed using the Psoriasis Area and Severity Index (PASI), in which erythema is graded subjectively on a 0-4 scale. This visual assessment is prone to significant inter- and intra-rater variability.\n\nAlthough objective tools such as colorimeters provide accurate erythema measurement, their high cost limits routine clinical use. Smartphone imaging combined with artificial intelligence (AI) offers a practical alternative for objective assessment. However, variability in lighting conditions can affect image consistency. Incorporating a color calibration card enables accurate color normalization.\n\nThis study aims to develop and validate an AI-based system for measuring erythema in psoriatic lesions using smartphone images with a color card, compared against a standard colorimeter to assess validity and reliability.",[54],"Psoriasis","NOT_YET_RECRUITING","2026-03-20",{"date":58,"type":59},"2026-03-27","ACTUAL",{"date":61,"type":49},"2026-04-20",{"date":63,"type":49},"2027-04-20",{"name":5,"class":6},1]