Faculty Bibliography

Generative AI, particularly large language models (LLMs), is reshaping clinical workflows in dermatology. However, cloud-based commercial models pose persistent challenges to Health Insurance Portability and Accountability Act (HIPAA) compliance, especially in dermatology, where protected health information (PHI) extends beyond text to clinical photographs, dermoscopic images, and total-body photography that may capture identifiable anatomical features and document conditions carrying social stigma. Locally hosted, open-weight LLMs that are run within the institution's own infrastructure offer dermatology practices a pathway to leverage AI capabilities while retaining full control of their data. This viewpoint synthesizes evidence on when locally hosted, open-weight LLMs should be preferred for dermatologic workflows, when cloud deployment may remain preferable, and how multimodal AI fits into a coherent local deployment strategy. We advance 4 arguments. First, model compression techniques (knowledge distillation, structured pruning, and low-bit quantization) together with mixture-of-experts architectures have lowered hardware thresholds enough that 7- to 33-billion-parameter models now run on consumer-grade workstations with modest neural processing units or graphics processing units. Second, dermatology is fundamentally a visual specialty, and a credible local deployment strategy must integrate LLMs with vision models, including convolutional neural networks, vision transformers, vision-language models, and dermatology-specific foundation models such as PanDerm and medical multimodal models such as MedGemma. Third, locally hosted, open-weight models confer specific advantages for dermatology, including complete institutional control of clinical images, freedom from vendor model deprecation that disrupts validated workflows, and the ability to audit and fine-tune models to address well-documented performance gaps in skin of color. Fourth, local deployment is not a panacea; cloud models remain preferable for some tasks, and local deployment introduces governance challenges (heterogeneity across practices, model drift, and quantization-induced accuracy loss) that require structured mitigation through validated reporting frameworks such as CONSORT-AI (Consolidated Standards of Reporting Trials), SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials), DECIDE-AI (Developmental and Exploratory Clinical Investigations of Decision support systems driven by AI), and TRIPOD+AI (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis), as well as retrieval-augmented generation and federated learning approaches. We situate these arguments within the international regulatory landscape, including the European Union's General Data Protection Regulation, the European Union AI Act, and Germany's Digitale Gesundheitsanwendungen (DiGA) framework, in addition to HIPAA. We provide quantitative cost examples showing that current consumer hardware capable of running 14- to 33-billion-parameter models can be acquired for roughly the price of 1 to 2 years of enterprise cloud-AI subscriptions. We close by mapping a practical implementation pathway and identifying near-term research priorities. Locally hosted, open-weight LLMs that are deployed thoughtfully and within governance frameworks offer dermatology practices a credible route to harness generative AI while preserving regulatory compliance, equity across skin types, and the dermatologist-patient relationship.

Allergic contact dermatitis (ACD) to personal care products (PCPs) represents a significant and growing clinical challenge, with increasing use of diverse PCPs and their expanding range of ingredients. Common allergenic components include fragrances, botanicals, preservatives, surfactants, emollients, emulsifiers, vitamins, and ultraviolet (UV) filters. Patch testing remains the gold standard for diagnosing ACD and identifying causative allergens, but traditional panels often fail to capture emerging PCP-related allergens. This review highlights key established and emerging PCP allergens, such as limonene and linalool hydroperoxides, sodium benzoate, octocrylene, and benzophenone-4. Strategies are discussed to optimize diagnostic accuracy through targeted series and repeated open application tests. Patient education about PCP labeling is paramount when assisting patients with allergen avoidance. Clinicians must balance precise allergen identification with practical management knowledge to improve outcomes in PCP-related ACD.

The diagnosis of dermatologic conditions typically hinges on the examination of visibly apparent skin abnormalities. On occasion, dermatologists can aid in diagnosing the "invisible" by performing biopsies of skin that seems clinically normal, with the hope that histologic clues only apparent in tissue samples-and not by the naked eye-may yield helpful diagnostic information. This narrative review discusses the utility of random, normal skin biopsy in the diagnosis of a variety of conditions for which this method has been described. Herein, we review the available literature on the use of normal skin biopsy for Alport syndrome, amyloidosis, atypical hemolytic uremic syndrome; cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, intravascular lymphoma, lysosomal storage disorders, pseudoxanthoma elasticum, rabies, and small fiber neuropathies.

This case describes a 50-year-old kidney transplant recipient with subacute development of erythematous-to-violaceous skin lesions on the face, trunk, and extremities, accompanied by malaise, myalgia, and arthralgia. Histopathologic analysis of skin biopsies revealed characteristic vascular proliferation consistent with bacillary angiomatosis (BA), a rare angioproliferative disease caused by Bartonella henselae or Bartonella quintana infection, primarily affecting immunocompromised individuals. The patient was treated successfully with oral doxycycline, resulting in the resolution of symptoms and lesions. BA is typically transmitted via cats and presents variably, including cutaneous angioproliferative lesions, hepatic or splenic involvement, and endocarditis. Diagnosis relies on histopathology with specialized staining and molecular testing, as culture and serologies are often insufficient. Treatment typically involves prolonged antibiotic therapy, emphasizing the importance of early recognition in immunosuppressed patients, including solid organ transplant recipients, to prevent complications.

Cutaneous lupus erythematosus (CLE) is an autoimmune disease with diverse clinical manifestations, including patchy hair loss resembling alopecia areata (AA). This report describes two cases of CLE presenting as AA mimickers, emphasizing the need to consider CLE in differential diagnosis for patchy hair loss. Early and accurate diagnosis is crucial for effective management and preventing scarring alopecia. J Drugs Dermatol. 2025;24(3):324-326. doi:10.36849/JDD.7793R1.