Ignite Creation Date:
2025-12-25 @ 3:30 AM
Ignite Modification Date:
2025-12-26 @ 2:12 AM
Study NCT ID:
NCT05682105
Status:
UNKNOWN
Last Update Posted:
2023-01-12
First Post:
2022-12-26
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Detection of Jaundice From Ocular Images Via Deep Learning
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D004066', 'term': 'Digestive System Diseases'}, {'id': 'D007565', 'term': 'Jaundice'}], 'ancestors': [{'id': 'D006932', 'term': 'Hyperbilirubinemia'}, {'id': 'D010335', 'term': 'Pathologic Processes'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}, {'id': 'D012877', 'term': 'Skin Manifestations'}, {'id': 'D012816', 'term': 'Signs and Symptoms'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 1633}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'UNKNOWN', 'lastKnownStatus': 'ACTIVE_NOT_RECRUITING', 'startDateStruct': {'date': '2018-12-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2023-01', 'completionDateStruct': {'date': '2023-06-30', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2023-01-10', 'studyFirstSubmitDate': '2022-12-26', 'studyFirstSubmitQcDate': '2023-01-10', 'lastUpdatePostDateStruct': {'date': '2023-01-12', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2023-01-12', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2022-10-30', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'area under the receiver operating characteristic curve of the deep learning system', 'timeFrame': 'baseline', 'description': 'The investigators will calculate the area under the receiver operating characteristic curve of deep learning system'}], 'secondaryOutcomes': [{'measure': 'sensitivity and specificity of the deep learning system', 'timeFrame': 'baseline', 'description': 'The investigators will calculate the sensitivity and specifity of deep learning system'}]}, 'oversightModule': {'oversightHasDmc': True, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Ophthalmology', 'Artificial Intelligence', 'ocualr image', 'Jaundice'], 'conditions': ['Ophthalmology', 'Artificial Intelligence', 'Hepatobiliary Disease']}, 'descriptionModule': {'briefSummary': "Our study presents a detection model predicting a diagnosis of jaundice (clinical jaundice and occult jaundice) trained on prospective cohort data from slit-lamp photos and smartphone photos, demonstrating the model's validity and assisting clinical workers in identifying patient underlying hepatobiliary diseases.", 'detailedDescription': "This study demonstrated that deep learning models could detect jaundice using ocular images in blood levels with reasonable accuracy, providing a non-invasive method for jaundice detection and recognition. This algorithm can assist clinical surgeons with daily follow-up visits and provide referral advice. It also highlights the algorithm's potential smartphone application in sizeable real-world population-based disease-detecting or telemedicine programs."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'PROBABILITY_SAMPLE', 'studyPopulation': 'This prospective, multicentre, observational study was led by Zhongshan Ophthalmic Centre (ZOC), Sun Yat-sen University, and conducted in three phases to collect data from participants from three surgery departments and three medical examination centres, including the Department of Hepatobiliary Surgery of the Third Affiliated Hospital of Sun Yat-sen University (HTH; Guangzhou, China), the Department of Infectious Diseases, Third Affiliated Hospital of Sun Yat-sen University (ITH; Guangzhou, China), the Department of Infectious Diseases, the Affiliated Huadu Hospital of Southern Medical University (HDH; Guangzhou, China), the Medical Centre of the Third Affiliated Hospital of Sun Yat-sen University(MCH; Guangzhou, China), Nantian Medical Centre of Aikang Health Care (NMC), and Huanshidong Medical Centre of Aikang Health Care (HMC).', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* The quality of slit-lamp images should be clinical acceptable. More than 90% of the slit-lamp image area, including three central regions (sclera, pupil, and lens) are easy to read and discriminate.\n\nExclusion Criteria:\n\n* Images with light leakage (\\>10% of the area), spots from lens flares or stains, and overexposure were excluded from further analysis'}, 'identificationModule': {'nctId': 'NCT05682105', 'briefTitle': 'Detection of Jaundice From Ocular Images Via Deep Learning', 'organization': {'class': 'OTHER', 'fullName': 'Sun Yat-sen University'}, 'officialTitle': 'Detection of Jaundice From Ocular Images Via Deep Learning : a Prospective, Multicenter Cohort Study', 'orgStudyIdInfo': {'id': 'AEHD-2022'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Development dataset', 'description': 'Slit-lamp images collected from the Department of Hepatobiliary Surgery of the Third Affiliated Hospital of Sun Yat-sen University(HTH)， Affiliated Huadu Hospital of Southern Medical University(HDH)， and Nantian Medical Centre of Aikang Health Care (NMC).'}, {'label': 'Testing dataset', 'description': 'Slit-lamp and smartphone images collected from the Department of Infectious Diseases, Third Affiliated Hospital of Sun Yat-sen University（ITH）， Huanshidong Medical Centre of Aikang Health Care， the Medical Centre of the Third Affiliated Hospital of Sun Yat-sen University(MCH).'}]}, 'contactsLocationsModule': {'locations': [{'zip': '510000', 'city': 'Guangzhou', 'state': 'Guangdong', 'country': 'China', 'facility': 'Zhongshan Ophthalmic Center', 'geoPoint': {'lat': 23.11667, 'lon': 113.25}}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Sun Yat-sen University', 'class': 'OTHER'}, 'collaborators': [{'name': 'Third Affiliated Hospital, Sun Yat-Sen University', 'class': 'OTHER'}, {'name': 'Affiliated Huadu Hospital of Southern Medical University', 'class': 'UNKNOWN'}, {'name': 'Aikang Health Care', 'class': 'UNKNOWN'}], 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Principal Investigator', 'investigatorFullName': 'Haotian Lin', 'investigatorAffiliation': 'Sun Yat-sen University'}}}}