Laser Surgery

Attention guided fair artificial intelligence modeling for skin cancer diagnosis.

Artificial intelligence (AI) has shown promise in dermatology, offering accurate and non-invasive diagnosis of skin cancer. While extensive research has addressed skin-tone bias, gender bias in dermatologic AI remains underexplored, potentially perpetuating diagnostic disparities. In this study, we developed LesionAttn, an algorithm designed to mitigate gender bias by directing model attention tow...

A validated custom pipeline for three-dimensional kidney stone renderings tocreate an open access repository.

Three-dimensional (3D) rendering of urologic pathology plays an important role in simulation-based education, surgical training, and computer vision research; however, a standardized, open-access repository of high-fidelity kidney stone models stratified by chemical composition is lacking. We developed and validated a reproducible photogrammetry-based pipeline to generate realistic 3D kidney stone...

A Hybrid AI-Mathematical approach for epidemic threshold prediction in metapopulation networks: Integrating physics-guided neural networks with spectral graph theory.

Predicting the epidemic threshold [Formula: see text] in contact networks is a central challenge in computational epidemiology. Classical structural a...

Improving Trauma Triage Accuracy with Large Language Models: A Comparison to Human Expert Decisions.

BACKGROUND: Accurate prehospital trauma triage and communication determine morbidity, mortality, and system efficiency. Advancements in large language...

The Irreducible Encounter: Human Skills, Artificial Intelligence, and the Future of Ophthalmic Care.

New Frontiers of Skin Ultrasound in Precision Medicine.

Ultrasound has emerged as a versatile, non-invasive imaging technique in dermatology, offering real-time, high-resolution visualization of cutaneous s...

Development and validation of a LightGBM-based model with risk stratification for predicting early recurrence after catheter ablation for atrial fibrillation.

BACKGROUND: Atrial fibrillation (AF) is the most prevalent sustained arrhythmia, yet tools for predicting early recurrence (ER) after catheter ablatio...

Localizing the Epileptogenic Zone Using SEEG-Based Excitation-Inhibition Dynamics and Spectral Features in Drug-Resistant Epilepsy: A Multicenter Retrospective Study.

Drug-resistant epilepsy (DRE) affects millions of people worldwide and remains a major therapeutic challenge, largely due to the difficulty in precise...

Artificial intelligence in dermatology: Clinical promise and environmental impact.

Artificial intelligence (AI) is reshaping dermatology through diagnostic image analysis, clinical documentation, and patient communication tools. Howe...

Evaluating the quality of artificial intelligence responses to psoriasis-related clinical and patient questions: a comparative study of ChatGPT, Gemini, and Microsoft Copilot.

BACKGROUND: Patient use of artificial intelligence (AI) chatbots for dermatologic information is increasing, but their performance on psoriasis-relate...

Enhanced Diagnosis of Generalized Pustular Psoriasis With the Legit.Health Device as a Diagnosis Support Tool: Multireader Multicase Study.

BACKGROUND: Generalized pustular psoriasis (GPP) is a rare, chronic, systemic inflammatory disease with an unpredictable and heterogeneous clinical co...

Informatics-Based Psychotherapeutic and Psychiatric Interventions in Dermatology: Scoping Review of Impacts on Skin Disease Severity and Mental Health Outcomes.

BACKGROUND: Chronic dermatologic conditions such as psoriasis, atopic dermatitis, and hidradenitis suppurativa are associated with a high burden of ps...

Evaluating reasoning in multimodal large language models for ophthalmology: a bilingual benchmark study using clinical vignettes and imaging.

BACKGROUND: Large language models (LLMs) excel in text-based medical exams, but their ability to integrate multimodal data, critical for ophthalmology...

Development of a machine learning model using systemic and ophthalmic parameters to detect sleep-disordered breathing in glaucoma patients.

PURPOSE: To develop and validate a machine-learning model using systemic and ophthalmic parameters that predicts sleep-disordered breathing (SDB) in p...

Whole anterior visual pathway segmentation from high-resolution MRI using artificial intelligence.

OBJECTIVE: Manual segmentation of the whole anterior visual pathway (aVP) from high-resolution magnetic resonance imaging (MRI) is time-consuming and ...

Performance Evaluation of GPT-5, Grok 4, and DeepSeek R1 in Interpreting Complete Blood Count Reports for Hematologic Diseases: Retrospective Comparative Study.

BACKGROUND: Large language models (LLMs) demonstrate potential in the laboratory, yet rigorous clinical evaluation remains limited. The opacity of LLM...

Reply to Kristoffer Mazanti Cold, Lars Konge, and Sarah Hjartbro Bube's Letter to the Editor re. Roessler N, Miszczyk M, Miyajima K, et al. Harnessing Artificial Intelligence for Risk Stratification and Outcome Prediction in Urologic Cancers: A Systematic Review. Eur Urol Focus. In press. http://dx.doi.org/10.1016/j.euf.2025.12.007.

Large Language Model Authorship in Ophthalmic Publications.

PURPOSE: To assess for the likely presence of artificial intelligence (AI)-generated text in the published ophthalmology literature. METHODS: Abstract...

Dnq-unet: a two-level fusion framework for few-shot domain adaptation in cervical cancer CTV segmentation.

To develop and validate a two-level hierarchical fusion architecture enabling efficient few-shot domain adaptation for cervical cancer clinical target...

Limits of Artificial Intelligence Models for Skin Cancer Diagnosis in Realistic Settings.

IMPORTANCE: Artificial intelligence (AI) systems for skin cancer detection perform well in controlled settings but frequently underperform in everyday...