United States Medical Licensing Examination Step 2 Clinical Knowledge and Research Productivity in Dermatology Residency Applications in the Post-Step 1 Era: Analysis of Match Outcomes From 2020 to 2024.

In recent years, the evaluation metrics for dermatology residency applications have changed, particularly following the transition of the United States Medical Licensing Examination (USMLE) Step 1 to a pass/fail grading system. This retrospective analysis examines dermatology residency match data from 2020 to 2024, focusing on trends in USMLE Step 2 Clinical Knowledge (CK) scores and research publications. Data extracted from the National Resident Matching Program documents revealed a notable increase in unmatched applicants with Step 2 CK scores above 250 and a decrease in matched applicants with similar scores.

Artificial intelligence in melanoma diagnosis: ethical considerations and clinical implementation.

The use of artificial intelligence (AI) in dermatology, particularly for the diagnosis of melanoma, has demonstrated potential in improving early detection of cancer. Current AI-based systems, such as DermaSensor and Nevisense, have shown high sensitivity. In addition, open-source models like All Data Are Ext (ADAE) continue to show promise.

Interdisciplinary approaches to diagnosing oral cavity skin cancers: The Dentist's involvement in detecting dermatological conditions.

Oral cavity skin cancers, including basal cell carcinoma, squamous cell carcinoma, Kaposi sarcoma, and melanoma, can be life-threatening if not detected early. Dentists play a crucial role in identifying these malignancies during extra- & intra-oral examinations. This viewpoint highlights the need for interdisciplinary collaboration between dentists and dermatologists to improve early diagnosis and treatment outcomes.

From toasted skin to tumors: a retrospective nationwide case-control analysis investigating the link between erythema ab igne and various skin cancers.

This study investigated erythema ab igne (EAI) and comorbid skin cancers. Each EAI case, searched by ICD-10-CM code L59.0 in the All of Us database, was compared to four controls, matched by sex at birth, age, and self-identified race/ethnicity.

The potential impact of ACOG guideline changes on genital melanoma detection rates in females: a retrospective cross-sectional analysis and implications for clinical practice.

Genital melanoma (GM) is a rare but aggressive cancer that accounts for less than 5% of vaginal cancers and 0.2-0.8% of all melanomas in the United States.