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Skin conditions affect 1.9 billion people. Because of a shortage of dermatologists, most cases are seen instead by general practitioners with lower diagnostic accuracy. We present a deep learning system (DLS) to provide a differential diagnosis of skin conditions using 16,114 de-identified cases (photographs and clinical data) from a teledermatology practice serving 17 sites. The DLS distinguishes between 26 common skin conditions, representing 80% of cases seen in primary care, while also providing a secondary prediction covering 419 skin conditions. On 963 validation cases, where a rotating panel of three board-certified dermatologists defined the reference standard, the DLS was non-inferior to six other dermatologists and superior to six primary care physicians (PCPs) and six nurse practitioners (NPs) (top-1 accuracy: 0.66 DLS, 0.63 dermatologists, 0.44 PCPs and 0.40 NPs). These results highlight the potential of the DLS to assist general practitioners in diagnosing skin conditions. A deep learning system able to identify the most common skin conditions may help clinicians in making more accurate diagnoses in routine clinical practice

Seborrheic dermatitis is a common skin condition in infants, adolescents, and adults. The characteristic symptoms—scaling, erythema, and itching—occur most often on the scalp, face, chest, back, axilla, and groin. Seborrheic dermatitis is a clinical diagnosis based on the location and appearance of the lesions. The skin changes are thought to result from an inflammatory response to a common skin organism, Malassezia yeast. Treatment with antifungal agents such as topical ketoconazole is the mainstay of therapy for seborrheic dermatitis of the face and body. Because of possible adverse effects, anti-inflammatory agents such as topical corticosteroids and calcineurin inhibitors should be used only for short durations. Several over-the-counter shampoos are available for treatment of seborrheic dermatitis of the scalp, and patients should be directed to initiate therapy with one of these agents. Antifungal shampoos (long-term) and topical corticosteroids (short-term) can be used as second-line agents for treatment of scalp seborrheic dermatitis.

Seborrheic dermatitis is a common, chronic relapsing skin condition that predominantly affects areas of the body that are rich in sebaceous glands. Clinically, seborrheic dermatitis presents as symmetric, poorly defined erythematous patches with yellow, oily scales and fine, superficial desquamation (flaking). In people who have darker skin, erythema may be less apparent, and postinflammatory pigmentary changes might be a presenting sign with hypopigmented, slightly scaly areas. Seborrheic dermatitis of the scalp can be effectively treated with topical over-the-counter antifungal shampoos and prescription-strength antifungal or corticosteroid solutions, foams, or oils. Thick, scaly areas can be treated with keratolytic shampoos and lotions. Seborrheic dermatitis of the face and body can be treated with over-the-counter and prescription-strength antifungal creams, over-the-counter and prescription-strength corticosteroid creams and ointments, and calcineurin inhibitor cream or ointment. Neonatal seborrheic dermatitis is common and typically self-resolves by 6 months of age. Mild cases of the scalp (cradle cap) may be treated conservatively with mineral oil to loosen scale and gentle combing. More severe cases may overlap with atopic dermatitis and can be treated with topical antifungals or topical corticosteroids.

Zinc pyrithione (ZnPT) is an anti-fungal drug delivered as a microparticle to skin epithelia. It is one of the most widely used ingredients worldwide in medicated shampoo for treating dandruff and seborrheic dermatitis (SD), a disorder with symptoms that include skin flaking, erythema and pruritus. SD is a multi-factorial disease driven by microbiol dysbiosis, primarily involving Malassezia yeast. Anti-fungal activity of ZnPT depends on the cutaneous availability of bioactive monomeric molecular species, occurring upon particle dissolution. The success of ZnPT as a topical therapeutic is underscored by the way it balances treatment efficacy with formulation safety. This review demonstrates how ZnPT achieves this balance, by integrating the current understanding of SD pathogenesis with an up-to-date analysis of ZnPT pharmacology, therapeutics and toxicology. ZnPT has anti-fungal activity with an average in vitro minimum inhibitory concentration of 10–15 ppm against the most abundant scalp skin Malassezia species (Malassezia globosa and Malassezia restrica). Efficacy is dependent on the targeted delivery of ZnPT to the skin sites where these yeasts reside, including the scalp surface and hair follicle infundibulum. Imaging and quantitative analysis tools have been fundamental for critically evaluating the therapeutic performance and safety of topical ZnPT formulations. Toxicologic investigations have focused on understanding the risk of local and systemic adverse effects following exposure from percutaneous penetration. Future research is expected to yield further advances in ZnPT formulations for SD and also include re-purposing towards a range of other dermatologic applications, which is likely to have significant clinical impact.

Skin diseases are one of the most common health problems that affect people of all ages around the world and significantly reduce the quality of life of individuals. Diseases of eczema, seborrheic dermatitis and skin cancer need to be diagnosed and correctly classified promptly. This issue, which is of great importance in terms of control and practical and effective treatment, is the study’s starting point. The study included 693 individuals with eczema, 750 with skin cancer and 770 with seborrheic dermatitis. In the study, which focused on the classification of 3 different skin diseases, the Relief algorithm was used to increase the classification success and to ensure the selection of more meaningful qualities. With AlexNet with cross-validation, the accuracy rate was 89.39% for 80% training and 20% test rates. When SVM classification with the Relief algorithm was used for the same rates, the accuracy rate was 92.10%. In the analysis performed on the ISIC 2017 dataset, the accuracy rate is 89.16% for 80% training and 20% test rate. When the training and test rate was changed to 70% training and 30% test rate, the accuracy rate was 91.11%. It was observed that SVM classification with Relief’s algorithm offers higher accuracy rates than other methods. The proposed model provides an original contribution to the literature, particularly through its integration of feature selection and a simplified architecture. This high success rate reveals that deep learning is an effective method in classifying skin diseases and the transfer learning process and will reduce the mortality rates due to cancer diseases with early and effective treatment while enabling skin diseases to be easily distinguished.

Prior research has indicated a link between seborrheic dermatitis (SD) and dysregulated immune responses; however, the causal linkage between this association and certain immune cell features has yet to be thoroughly clarified. This study seeks to examine the potential causal influence of immune cell characteristics on the pathogenesis of seborrheic dermatitis (SD) and to evaluate if these characteristics can function as biomarkers for early diagnosis and therapy. Data mining was performed using the Genome-Wide Association Study (GWAS) Catalog database to select 731 immune cell features for exposure variables and seborrheic dermatitis for the outcome variable in a forward Mendelian Randomization (MR) study. In a reverse MR analysis, seborrheic dermatitis was designated as the exposure factor, while the significant immune cell traits recognized by a forward MR analysis were used as outcome factors to exclude potential reverse causality. Five MR analyses were carried out by utilizing methods such as inverse variance weighting (IVW). Additionally, false discovery rate (FDR) correction, heterogeneity testing, level-dependent pleiotropy analysis, and sensitivity analysis were conducted. This study identified 11 immune traits causally associated with seborrheic dermatitis (SD). Specifically, five immune phenotypes were found to have been linking to a lower risk of SD: CD24on transitional, CD28 − DN(CD4 − CD8−)%T cell, CD45RA − CD28 − CD8br AC, Resting Treg%CD4, SSC − A on NKT. Conversely, six immunized traits have been shown with a greater risk of SD: CD127 − CD8br AC, CD20on CD24 + CD27+, CD27on IgD − CD38br, CD27on unsw mem, CD28 + DN(CD4 − CD8−)%T cell, HLA DR on CD33br HLA DR + CD14dim. The sensitivity analysis showed an absence of heterogeneity and level-dependent pleiotropy.This study demonstrates that specific immune cell traits not only correlate with SD but also provide valuable mechanistic insights into its pathogenesis. These immune traits also hold promise as biomarkers for early diagnosis, risk stratification, and personalized therapy. In addition, the findings provide new insights into immune mechanisms, highlighting the potential of targeted immunotherapies in SD treatment.

Seborrheic dermatitis (SD) is a common, burdensome inflammatory skin disorder. Little is known about the identity and quality of videos patients consume on social media to better understand and manage SD. We evaluated three social media platforms—YouTube, TikTok, and Instagram—for content, quality, and popularity. Search terms “seborrheic dermatitis,” “dandruff,” “cradle cap,” and “flaky scalp” identified videos on each platform. The first 50 videos for each keyword were analyzed. After screening, 147 YouTube, 132 Instagram, and 164 TikTok videos were included. Videos were characterized by upload source (healthcare provider/organization [HCP]/non-HCP), quality (accurate/misleading/non-informative), content (educational/personal xperience/entertainment/advertisement), and number of likes/views. Data were analyzed by chi square (categorical) or Kruskal–Wallis (continuous) tests. YouTube contained a higher proportion of videos vs. TikTok and Instagram that were made by HCPs (42.2/19.7/17.7%, respectively) and contained more accurate (52.4/28.0/32.9%), and educational (66.7/38.6/34.4%) content ( p <  0.0001 for all). Non-HCPs were responsible for creating the majority of videos across platforms along with most inaccurate/non-informative (65.9/86.8/78.6%) and non-educational (56.5/75.5/71.1%) content ( p <  0.0001 for all). Despite lower quality of content and information, TikTok videos had the highest mean views (2,418,872) and likes (184,395) ( p <  0.0001 for all). HCP vs. non-HCP-made videos were viewed more frequently only on YouTube. Though views and likes were common for all inaccurate and entertainment/advertisement content, they were most characteristic of TikTok and Instagram ( p <  0.0001). These results show a high volume of SD video consumption across all platforms, especially those with lower quality and less informative content, and significant content difference across platforms. Additional studies are needed to better characterize online SD educational content and optimize HCP-led video creation and patient video consumption.

Seborrheic dermatitis (SD) poses significant treatment challenges due to its chronic nature and the side effects associated with long-term use of conventional therapies like topical corticosteroids. In the search for alternative treatments, exosomes, particularly those derived from rose stem cells (RSCEs), offer a promising avenue due to their potential in managing chronic skin conditions. This case report examines the efficacy of a topical moisturizer containing RSCEs in treating a patient with refractory SD, aiming to provide an alternative treatment pathway. A 40-year-old male with a long-standing history of SD, unresponsive to traditional treatments, underwent a novel treatment regimen. This regimen included an initial topical application of 2.5 mL of RSCEs followed by a maintenance phase involving the application of a RSCE-containing moisturizer. Clinical outcomes were assessed through the Patient's Global Assessment (PGA) and Investigator's Global Assessment (IGA) scores, along with evaluations of scaling and erythema. Remarkable clinical improvement was noted as early as 1-day post-treatment, with significant reductions in redness, scaling, and itching. The patient experienced sustained relief throughout the 6-month follow-up, with a recurrence in the sixth month that was less severe than previous flare-ups. This demonstrated not only the efficacy of RSCEs in symptom management but also their potential in extending remission periods. The chronic management of SD can benefit from innovative treatments like the RSCE-containing moisturizer, as shown in this case report. While the observed outcomes are promising, indicating substantial improvements in skin condition and symptom management, larger controlled studies are necessary to validate the therapeutic potential of exosome-containing moisturizers fully. This case underscores the need for alternative therapies in SD treatment, highlighting the role of exosomes as a viable option.

To evaluate the three symptom indicators of scalp seborrheic dermatitis (SSD), namely scalp flaking, maximum erythema area, and pruritus, to develop a \"16-point scale,\" to explore its relationship with the severity of SSD, and verify the reliability of the 16-point scale. A dermatologist evaluated patients with SSD using a 16-point scale, and statistically analyzed the collected data with the help of SPSS 26.0 software. The measurement data are expressed as (mean ± SD), and the intergroup comparison was done using a non-parametric test. We performed the correlation analysis using the bivariate correlation analysis method, and the relationship among non-normal distribution data variables were analyzed using Spearman's correlation coefficient. p < 0.05 indicated that the difference was statistically significant. The total score of the \"16-point scale\" strongly correlated with the severity of disease, where scalp flaking had the strongest correlation. As compared with a single score, the correlation of the total score with the severity of disease was higher. The scoring range for mild patients was (0, 5], that for moderate patients was (5, 9], and that for severe patients was (9, 16]. A \"16-point scale\", consisting of items for adherent scalp flaking (0-10), maximum erythema area (0-3), and pruritus (0-3), was used to score the patients with SSD, and the total score was strongly correlated with and differentiated the severity of SSD. Recommended evaluation criteria: a total score of 0-5 points indicates mild SSD, 6-9 points indicates moderate SSD, 10-16 points indicates severe SSD. These criteria can help to standardize disease diagnosis and treatment, and efficacy assessment.