View clinical trials related to Skin Diseases.
Filter by:This multi-arm, multi-site study investigates the safety, tolerability, and efficacy of stem cell therapy for the treatment of various acute and chronic conditions. Clinically observed initial findings and an extensive body of research indicate regenerative treatments are both safe and effective for the treatment of multiple conditions.
Skin biopsy is the main method to diagnose skin tumors, skin inflammation, and pigmented diseases. However, biopsy is an invasive method that can cause wounds and scars. Optical coherent tomography (OCT) technology is a fast, non-invasive, non-radioactive, and label-free imaging method. This technology generates real-time images of living tissue by detecting the variations in the refractive indexes of various components in soft tissues. Recently, there is a breakthrough progress that the newly designed ultrahigh resolution OCT can provide in vivo cellular resolution similar to histopathological sections in the high magnification. In our previous clinical trial "Early feasibility study: application of OCT imaging in dermatology" (approved by IRB of MacKay Memorial Hospital, no. 17CT062Be), it showed characteristic features of different skin inflammatory diseases and tumors can be distinguished successfully in tomograms. There were no adverse event or serious adverse event in this trial. Artificial intelligence technologies have been used widely in the image analysis in recent years. Hence, we aim to collect OCT tomograms of common skin inflammatory diseases, skin tumors, and pigmented diseases, and compare with normal skin for machine learning. We expect the integration of tomograms with deep learning artificial intelligence may assist identifying histological features in these images and provide new alternative way for non-invasive diagnosis in dermatology.
The objectives of this enabling study are to characterize the wheal and flare responses over time following skin challenges with ascending concentrations of Substance P. This will be a 2-part study: Part 1 will aid in the understanding of the wheal and flare responses following Substance P. Part 2 will investigate the variability of the responses. Participants may be enrolled into Part 1 or Part 2, not both.
This sample collection study will recruit subjects with a variety of skin conditions from up to 15 geographically dispersed sites in the United States. Skin samples will be collected with the DermTech Adhesive Patch Kit from both lesional and non-lesional skin. Subjects may also be asked to return at a future data for additional collections. Collected skin samples will be analyzed for gene expression information, DNA and the microbiome.
The principal objective is to measure the degree to which oral microstomia caused by sclerosing skin disease improves after treating patients with local hyaluronidase injections. Investigator will determine improvements in oral aperture by measuring the centimeters of the height of oral opening. The secondary objectives are: Investigator will aim to assess changes in quality of life and functionality, by serial calculations of the Mouth Handicap in Systemic Sclerosis (MHISS). In addition, investigator would like to investigate how many treatments are required prior to treatment efficacy plateauing. Since there is minimal data on the use of hyaluronidase for oral microstomia, it is not yet clear how many treatments are ideally required for maximal effect. Patients will be brought in monthly for photographs, examination, assessment, and treatment. Our hypothesis is that hyaluronidase injections will significantly improve patients' ability to open their mouths and oral functionality. It remains unclear how many treatments will be required for maximal effect.
Background: Deep neural networks (DNN) has been applied to many kinds of skin diseases in experimental settings. Objective: The objective of this study is to confirm the augmentation of deep neural networks for the diagnosis of skin diseases in non-dermatologist physicians in a real-world setting. Methods: A total of 40 non-dermatologist physicians in a single tertiary care hospital will be enrolled. They will be randomized to a DNN group and control group. By comparing two groups, the investigators will estimate the effect of using deep neural networks on the diagnosis of skin disease in terms of accuracy.
Acute radiodermatitis (ARD) is a distressing and painful skin reaction that occurs in 95% of the patients undergoing radiotherapy (RT). To date, there is still no general approved guideline for the prevention and management of acute radiodermatitis. The 3M™ Cavilon™ Advanced Skin Protectant is a novel skin barrier protectant that acts as a physical barrier against abrasion, moisture, and irritants. Moreover, it enables an environment for wound healing. The aim of this study is to evaluate the effectiveness of 3M™ Cavilon™ Advanced Skin Protectant in the prevention and management of ARD in patients with head and neck cancer.
Recent research has reported that the maple leaf extract exhibits anti-aging effects by inhibiting elastase activity, thereby preventing the breakdown of elastin and interfering with the formation of wrinkles. Red maple leaf extract contains phenolic compounds known as glucitol-core-containing gallotannins (GCGs) which help reduce the appearance of wrinkles and may decrease skin inflammation, dark spots and pigmentation. The objective of this study is to examine the effects of topical Maplifa on the cosmetic appearance of facial lines, redness and skin tone.
Background: Dermatological conditions are a relevant health problem. Machine learning models are increasingly being applied to dermatology as a diagnostic decision support tool using image analysis, specially for skin cancer detection and classification. Objective: The objective of this study is to perform a prospective validation of an image analysis ML model, which is capable of screening 44 different skin disease types, comparing its diagnostic capacity with that of General Practitioners (GPs) and dermatologists. Methods: In this prospective study 100 consecutive patients who visit a participant GP with a skin problem in central Catalonia will be recruited, data collection is planned to last 7 months. Skin diseases anonymized pictures will be taken and introduced in the ML model interface, which will return top 5 accuracy diagnosis. The same image will be also sent as a teledermatology consultation, following the current workflow. GP, ML model and dermatologist/s assessments will be compared to calculate the precision, sensitivity, specificity and accuracy of the ML model.
This study examines the effect of IL-23 blockade with Tildrakizumab on the immune cells of psoriatic skin lesions.