Non-venereal genital dermatoses and their impact on quality of life-A cross-sectional study

The performance of an artificial intelligence-based computer vision mobile application for the image diagnosis of genital dermatoses: a prospective cross-sectional study

BACKGROUND

There is a huge demand-supply gap between the incidence of genital dermatoses (including sexually transmitted infections and non-venereal genital dermatoses) and physicians trained to manage them.

OBJECTIVES

To find out the performance of an artificial intelligence (AI)-based mobile application in the image diagnosis of genital dermatoses, and to compare it with primary care physicians (PCPs) and dermatologists.

METHODS

Photos of the genital diseases of consecutive patients presenting to the STD and genital diseases clinic were included. The gold standard diagnosis was established by the consensus of two certified dermatologists after examination and one positive investigation. Image diagnoses by the DermaAId application, two PCPs, and two dermatologists were recorded and compared to the gold standard diagnosis and to each other.

RESULTS

A total of 257 genital disease images, including 95 (37.0%) anogenital warts, 60 (22.2%) lichen sclerosus, 20 (7.8%) anogenital herpes, 15 (5.8%) tinea cruris, 14 (5.4%) molluscum contagiosum, 9 (3.5%) candidiasis, 8 (3.1%) scabies, 6 (2.3%) squamous cell carcinomas, were included. The top-1 correct diagnosis rate of the application was 68.9%, compared to the 50.4% of the PCPs and 73.2% of the dermatologists. The application significantly outperformed PCPs with regard to the correlation with the gold standard diagnosis (P < 0.0001), and matched that of the dermatologists.

CONCLUSIONS

AI-based image diagnosis platforms can potentially be a low-cost rapid decision support tool for PCPs, integrated with syndromic management programs and direct-to-consumer services, and address healthcare inequities in managing genital dermatoses.

The Role and Impact of Artificial Intelligence in Addressing Sexually Transmitted Infections, Nonvenereal Genital Diseases, Sexual Health, and Wellness

The potential of artificial intelligence (AI) in diagnosing and managing sexually transmitted infections (STIs), nonvenereal genital diseases, and overall sexual health is immense. AI shows promise in STI screening and diagnosis through image recognition and patient data analysis, potentially increasing diagnostic accuracy while ensuring inclusivity. AI can fuel the transformation of e-health and direct-to-consumer services, enhancing targeted screening and personalized interventions while improving the user-friendliness of services. There is a significant role for AI in sexual education, particularly its use in interactive, empathetic chatbots. AI's integration into health care as a decision support tool for primary health-care providers can boost real-time diagnostic accuracy. Furthermore, AI's use in big data can enhance real-time epidemiology, predictive analysis, and directed interventions at population levels. However, challenges such as real-world diagnostic accuracy, liability, privacy concerns, and ethical dilemmas persist. Future directions include an emphasis on inclusivity, language accommodation, and swift research-to-practice transitions. Collaboration among policymakers, researchers, and health-care providers is needed to leverage AI's transformative potential in sexual health.

Quality of life measurement in vitiligo. Position statement of the European Academy of Dermatology and Venereology Task Force on Quality of Life and Patient Oriented Outcomes with external experts

Members of the European Academy of Dermatology and Venereology (EADV) Task Force on Quality of Life (QoL) and Patient Oriented Outcomes reviewed the instruments available for health-related (HR) QoL assessment in vitiligo and together with external vitiligo experts (including representatives of the EADV Vitiligo Task Force) have made practical recommendations concerning the assessment of QoL in vitiligo patients. The Dermatology Life Quality Index (DLQI) was the most frequently used HRQoL instrument, making comparison of results between different countries possible. Several vitiligo-specific instruments were identified. The vitiligo Impact Scale (VIS) is an extensively validated vitiligo-specific HRQoL instrument with proposed minimal important change and clinical interpretation for VIS-22 scores. VIS-22 was developed for use in India, where there are some specific cultural beliefs concerning vitiligo. The EADV Task Force on QoL and Patient Oriented Outcomes recommends use of the DLQI and the Children's Dermatology Life Quality Index (CDLQI) as dermatology-specific instruments in vitiligo. There is a strong need for a valid (including cross-cultural validation) vitiligo-specific instrument that can be either a new instrument or the improvement of existing instruments. This validation must include the proof of responsiveness.