An observational study in Acne, Acne Vulgaris and Alopecia, Androgenetic, sponsored by AI Labs Group S.L. Recruiting at 1 site in Spain. Open to participants aged 16 Years and older. Per ClinicalTrials.gov, last updated 2024-03-19.
Sponsored by AI Labs Group S.L · Observational
Artificial intelligence (AI) based on imaging holds tremendous potential to enhance visual diagnostic accuracy in the medical field. Amid the COVID-19 pandemic, limited access to in-person healthcare services drove shifts in medical care, hastening the adoption of telemedicine. In this context, AI usage for triage and decision support may be crucial for professionals to manage workload and improve performance. In dermatology, pigmented lesions, acne, and alopecia are three recurring pathology groups with high demand in dermatological centers. Both triage, clinical evaluation, and patient follow-up require in-person resources and specialist dedication. Employing tools like AI can benefit these professionals in reducing such processes and optimizing workload.
Advancements in image recognition and interpretation, as well as in artificial intelligence, have spurred innovations in diagnosing various pathologies, including skin conditions. Computer-Aided Diagnosis (CAD) systems and other algorithm-based technologies have demonstrated the ability to classify lesion images with a competency comparable to that of an expert physician.
In this study, the Legit.Health tool, developed by AI LABS GROUP S.L., which utilizes artificial intelligence to optimize clinical flow and patient care processes for skin conditions, will be evaluated. The purpose of this tool is to automatically prioritize patients with greater urgency, assign the type of consultation (dermatological or aesthetic), enhance diagnostic capability and detection of malignant pigmented lesions in auxiliary staff, and provide a visual record (photograph) of the condition for later review by external experts.
Thus, the main objective of this study is to validate that Legit.Health, based on Artificial Intelligence, improves efficiency in clinical flow and patient care processes, thereby reducing time and cost of patient care through enhanced diagnostic accuracy and severity determination.
The secondary objectives focus on measuring the diagnostic performance of Legit.Health:
Demonstrate that Legit.Health enhances healthcare professionals\' ability to detect malignant or suspicious pigmented lesions.
Demonstrate that Legit.Health improves healthcare professionals\' ability and precision in measuring the degree of involvement in patients with female androgenetic alopecia.
Demonstrate that Legit.Health improves healthcare professionals\' ability and precision in measuring the degree of involvement in patients with acne.
Additionally, the study aims to assess the utility of this tool:
Automate the triage/initial assessment process in patients presenting with pigmented lesions.
Evaluate the reduction in healthcare resources usage by the center by reducing the number of triage consultations and directing the patient directly to the appropriate consultation (esthetic or dermatological).
Evaluate Legit.Health\'s usability by the patient. Demonstrate that Legit.Health increases specialist satisfaction. Evaluate the reduction in healthcare resources usage by reducing the number of triage consultations and directing the patient directly to the appropriate consultation, whether in aesthetic or dermatological settings.
Methodology Study Design Type This is an observational study, both prospective with a longitudinal character and retrospective case series.
Study Period This study estimates a recruitment period of 3 months. The total study duration is estimated at 6 months, including the previous time for retrospective analysis and the necessary time after recruiting the last subject for database closure and editing, data analysis, and preparation of the final study report.
The total study duration for each participant with pigmented lesions will be 1-3 months. The duration for patients with acne and alopecia will be 1 day.
Study Population Adult patients (≥ 18 years) with skin pathologies treated at the Dermatology Unit of IDEI.
Artificial intelligence (AI) based on images presents enormous potential for improving visual diagnostic accuracy in the medical field. During the COVID-19 pandemic, limited access to in-person healthcare services drove changes in medical care, accelerating the adoption of telemedicine. In this context, the use of AI for triage and decision support can be crucial for professionals to manage workload and improve performance. In dermatology, pigmented lesions, acne, and alopecia are three recurring pathology groups with high demand in a dermatological center. Both triage of these patients, clinical evaluation, and their follow-up require in-person resources and the dedication of the specialist and staff. The use of tools like AI can benefit these professionals in reducing these processes and optimizing the workload.
Advances in image recognition and interpretation, as well as in artificial intelligence, have driven innovations in diagnosing various pathologies, including skin conditions. Computer-Aided Diagnosis (CAD) systems and other algorithm-based technologies have demonstrated their ability to classify lesion images with a competency comparable to that of an expert physician.
In this study, the Legit.Health tool, developed by AI LABS GROUP S.L., which uses artificial intelligence to optimize clinical flow and the care process of patients with skin conditions, will be evaluated. The purpose of this tool is the automatic prioritization of patients with greater urgency, assigning them the type of consultation (dermatological or aesthetic), improving the diagnostic capacity and detection of malignant pigmented lesions in auxiliary staff, as well as providing a visual record (photograph) of the condition for later review by external experts.
Thus, the main objective of this study is to validate that the Legit.Health tool, based on Artificial Intelligence, improves efficiency in clinical flow and the care process of patients, reducing the time and cost of care per patient through enhanced diagnostic accuracy and determination of the degree of malignancy or severity.
The secondary objectives focus on measuring the diagnostic performance of Legit.Health:
Demonstrate that Legit.Health improves the ability of healthcare professionals to detect malignant or suspicious pigmented lesions.
Demonstrate that Legit.Health improves the ability and precision of healthcare professionals in measuring the degree of involvement in patients with female androgenetic alopecia.
Demonstrate that Legit.Health improves the ability and precision of healthcare professionals in measuring the degree of involvement in patients with acne.
Additionally, the study aims to assess the utility of this tool:
Automate the triage/initial assessment process in patients consulting for pigmented lesions.
Evaluate the reduction in healthcare resource usage by the center by reducing the number of triage consultations and directly referring the patient to the appropriate consultation (esthetic or dermatological).
Evaluate Legit.Health\'s usability by the patient. Demonstrate that Legit.Health increases specialist satisfaction. Evaluate the reduction in healthcare resource usage by reducing the number of triage consultations and directly referring the patient to the appropriate consultation, whether in aesthetic or dermatological settings.
Methodology:
Study Design Type:
This is an observational study, both prospective with a longitudinal character and retrospective case series.
Study Period:
This study estimates a recruitment period of 3 months.
The total study duration is estimated at 6 months, including the previous time for retrospective analysis and the necessary time after recruiting the last subject for database closure and editing, data analysis, and preparation of the final study report.
The total study duration for each participant with pigmented lesions will be 1-3 months. The duration for patients with acne and alopecia will be 1 day.
Study Population:
Adult patients (≥ 18 years) with skin pathologies treated at the Dermatology Unit of IDEI.
790 studies on the registry are indexed under Acne Vulgaris; 93 are open to participants now.
This study's planned enrollment of 150 is above the median of 88 across 95 observational studies indexed under Acne Vulgaris.
Browse Acne Vulgaris studies →AI Labs Group S.L is the lead sponsor of 8 studies on the registry; 1 is open to participants now.
Counted across the registry records on this site, refreshed daily.
Patients with pigmented lesions and suspected malignancy, patients diagnosed with inflammatory acne and women with androgenetic alopecia. All these people will be treated at the dermatology service of IDEI hospitals
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
Patients treated at IDEI hospitals and with pigments skin lesions, which are suspected malignancy. The practitioners will take a photo of the lesion and upload into the tool so as to confirm both the diagnosis and suspicion of malignancy
Patients treated at IDEI hospitals and diagnosed with acne. Practitioners will take a photo of patients' face and upload it into the tool so as to check the severity of acne and compare it with the gold standard
Patients treated at IDEI hospitals and diagnosed with femenine androgenetic alopecia. Practitioners will take a photo of the top of the head and upload it into the tool so as to check the severity of alopecia and compare it with the gold standard
Concordance between the physician's diagnosis and that of the tool.
Analysis of concordance between the diagnosis issued by the dermatologist and that determined by the Legit.Health tool.
Time frame: At the moment of enrollment up to 1 year
Agreement of detected malignancy between the dermatologist and Legit.Health tool
Correlation analysis of the suspected malignancy between the dermatologist and the Artificial Intelligence tool
Time frame: At the moment of enrollment up to 1 year
Acne severity
Severity of acne assessed by both physicians and Legit.Health tool through lesion counting. A correlation analysis will be performed to check differences of criteria between them
Time frame: At the moment of enrollment up to 1 year
Severity of alopecia
Severity of androgenetic alopecia assessed by both physicians and Legit.Health tool with the Ludwig scale. A correlation analysis will be performed to check differences of criteria between them
Time frame: At the moment of enrollment up to 1 year
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