AI in Dermatology Summit 2026

• Welcome address (Vice-Rector for Research and Innovation at the Medical University Vienna Michaela Fritz, Summit Chair Harald Kittler)
• The AI-powered evolution of research and practice in dermatology: A look back at the past ten years (Allan C. Halpern)

Chairs: Peter Soyer, Wolfgang Weninger

• Integrating AI into clinical workflows: Where we stand and what gaps remain (Josep Malvehy)
• AI-assisted detection and early diagnosis of skin cancer (Victoria Mar)
• Scaling dermatological care with AI: Mobile applications and virtual platforms (Tobias Sangers)
• Beyond skin cancer: Applied AI support for inflammatory skin conditions (Alexander Navarini)

Telemedicine 
10:50-10:52   AI-Enabled Asynchronous Teledermatology within Interoperable Digital Ecosystems
10:54-10:56   Diagnostic performance of human-artificial intelligence collaboration in teledermoscopy
10:58-11:00   Impact of an artificial intelligence as a medical device community pathway on urgent suspected skin cancer referral demand
11:02-11:04   Diagnostic concordance of text-based AI in teledermatology
11:06-11:08   Real-world performance of a CE Class III Artificial Intelligence as a Medical Device in suspicious skin lesions
11:10-11:12   Explainable AI in Dermatology: Models and Devices to Support Clinical Practice

Chairs: Harald Kittler, Ralph Braun

• Data quality and annotation: Building robust datasets for dermatology (Philipp Tschandl)
• Inclusive AI in dermatology: Confronting bias and data gaps (Roxana Daneshjou)
• Benchmarking and validation: Standards for evaluating AI in dermatology (Veronica Rotemberg)
• Trustworthy general-purpose AI: European and global perspectives (Matthias Samwald)

Chairs: Harald Kittler, Ralph Braun

Innovation & Science Slam:

• Preoperative assessment of melanoma thickness using AI – A prospective clinical trial (Filippos Giannopoulos)
• From 2D Images to 3D Intelligence: The Future of AI in Dermatology and Skin Cancer (Maryam Sadeghi)
• Making It Real: The Leadership Challenge of Clinical AI Deployment (Julia K Schofield)
• From AI to Augmented Intelligence: Insights from the DEXI Challenge (Lara Valeska Maul-Duwendag)
• AI-assisted margin definition of basal cell carcinomas during micrographic surgery using LC-OCT (Julia Welzel)
• Image-Based Prediction of Melanoma Prognosis Using Machine Learning (Konstantinos Lallas)
• Interactive, fully interpretable AI assistant improves diagnostic and management accuracy in challenging pigmented skin lesions (Lukasz Szyc)

Validation and risk assessment 
13:35-13:37  Robustness of a marked-approved convolutional neural network for skin cancer diagnosis
13:39-13:41  Performance Evaluation of an Artificial Intelligence–Based Dermoscopic Image Analysis Program for Diagnostic Support of Skin Tumors
13:43-13:45   External Validation and Characterization of a Convolutional Neural Network in a Large High-Risk Melanoma Cohort
13:47-13:49   Episode-Based Melanoma Risk Stratification Using Artificial Intelligence: Development and Validation of Time-Updated Prognostic Models
13:51-13:53   Expert-informed melanoma classification with dermoscopic and histopathologic data
13:55-13:57   Adapting a Multimodal Vision Foundation Model as a Universal Feature Extractor for Nail Pigmentation Diagnosis: A Non-Linear Probing Approach Using PanDerm

Multimodality and Attributes 
13:59-14:01   Systematic Benchmark of H&E-to-Transcriptomics Prediction in Skin Tissue
14:03-14:05   Raising the Standard for Skin Tone Annotations: a Comparison of the Fitzpatrick and Monk Scales
14:07-14:09   Quantitative Skin Attribute Grounding and Retrieval with Multimodal Large Language Models
14:11-14:13   Attention-Based Color Fusion in Dermoscopy AI
14:15-14:17   CD-RCM: Generalizable Continuous-Depth Novel View Synthesis for Reflectance Confocal Microscopy
14:19-14:21   Deep Learning-Based Hair Segmentation in UVFD Images

Chairs: Philipp Tschandl, Catarina Barata 

• xLSTM for LLM development (Günter Klambauer)
• Bridging imaging phenotypes and biological mechanisms (Georg Langs)
• Few shot, zero shot and continuous learning (Catarina Barata)
• Multimodal AI: Combining images, text and clinical data (Zongyuan Ge)
• Semantic coverage and domain adaptation for skin lesions (Moi Hoon Yap)
• Computational models/AI for epidemiologic questions (Nikolas Popper)

Digital Tools  
16:35-16:37   Med-Timeline: A Digital Tool for Assessing Drug Causality in Suspected Drug-Induced Skin Reactions
16:39-16:41   EffloraBot: An AI-Driven Interactive Learning Tool for Structured Dermatological Descriptions
16:43-16:45   Three Dimensions of Wound Healing: AI-Assisted Planimetric, Volumetric, and Clinimetric Assessment of Chronic Wounds
16:47-16:49   Injection Site Reaction Monitoring Reimagined: AI-Powered Detection and Inclusive Quantification
16:51-16:53   Establishing Research Priorities for Artificial Intelligence Approaches in Dermatology Using an e-Delphi Exercise
16:55-16:57   Smart Imaging and Deep Learning for Objective Psoriasis Lesion Scoring: A Scarletred Proof-of-Concept Study

Chairs: Veronica Rotemberg, Giuseppe Argenziano

• Reflection machines for AI-human collaboration (Sabine Köszegi)
• Explainability and transparency for AI-driven decision-making (Titus Brinker)
• The role of consumers in AI research (Monika Janda) 
• The AI-powered evolution of research and practice in dermatology: A look ahead to the next ten years (Allan C. Halpern)
• Bridging perspectives: An interactive panel discussion with clinicians, innovators and industry representatives (Moderator: Harald Kittler, Discussants: Giuseppe Argenziano, Dominique Du Crest, Sarah Haggenmüller, Sabine Köszegi, Anne Oyewole, Veronica Rotemberg)