Machine learning and artificial intelligence

All Items

• Multimodal Large Language Models in Dermatologic Diagnosis: A Game Changer or a Clinical Risk?

  Ümit Akpinar, Mehmet Semih Çelik, Ekrem Civaş, Yildiz Hayran, Başak Yalçın

  adv-2026-0586

• Impact of Large Language Model–assisted Differential Diagnosis on Clinical Decision-making in Dermatology: A Feasibility Study Using ChatGPT-5

  Yuto Yamamura, Kazuyasu Fujii, Chisa Nakashima, Atsushi Otsuka

  adv-2025-0180

• Predicting Melanoma Impact on the Swedish Healthcare System from the Adult Population Using Machine Learning on Registry Data

  Martin Gillstedt, Lena Stempfle, John Paoli, Fredrik D. Johansson, Sam Polesie

  adv44610

• The Use of Artificial Intelligence in Dermatology Systematic Reviews: A Comparative Analysis of Elicit Against Human Reviewers

  Jui Vyas, Jeffrey R. Johns, Emily Forrest, Mari Ann Hilliar, Sam Salek, Andrew Y. Finlay

  adv-2025-0213

• Discriminating Basal Cell Carcinoma with Only 20 Dermoscopic Images: A Few-shot, Self-supervised Approach

  Kyungho Paik, Sang Woong Youn, Jung-Im Na, Chang-Hun Huh, Jung Won Shin

  adv44686

• Impact of Long-term Stability on Mental Health in Adults with Atopic Dermatitis: A Cohort Study with Unsupervised Cluster Analysis

  Lea K. Nymand, Mia-Louise Nielsen, Maria Oberländer Christensen , Simon F. Thomsen, Jacob P. Thyssen, Alexander Egeberg

  adv43071

• Burden of Inflammatory Skin Diseases Based on GBD Data: China vs USA

  Yulin Zou, Kexin Liao, Stephan Traidl, Timo Buhl

  adv43753

• Identifying Mild-to-Moderate Atopic Dermatitis Using a Generic Machine Learning Approach: A Danish National Health Register Study

  Mie Sylow Liljendahl, Kristina Ibler, Christian Vestergaard, Lone Skov, Pavika Jain, Jan Håkon Rudolfsen, Ann Hærskjold, Mathias Torpet

  adv42250

• AI-assisted Total Body Dermoscopic Evaluation of Changes in Melanocytic Nevi during Pregnancy: A Prospective, Comparative Study of 2,799 Nevi

  Jelissa K. Peter, Fabrice Helfenstein, Sara E. Cerminara, Julia-Tatjana Maul, Mara L. Zehnder, Dagmar Jamiolkowski, Elisabeth Roider, Beda Mühleisen, Irene Hösli, Alexander A. Navarini, Lara V. Maul

  adv41025

• Assessing ChatGPT-4’s Capabilities in Generating Dermatology Board Examination Content: An Explorational Study

  Jonathan Shapiro, Anna Lyakhovitsky, Tamar Freud, Felix Pavlotsky, Ziyad Khamaysi, Yulia Valdman-Grinshpoun, Roni Dodiuk-Gad, Ilan Goldberg, Arieh Ingber, Baruch Kaplan, Emily Avitan-Hersh

  adv41208

• Use of Social Media by the Public Regarding Skin Health: Effects on Dermatological Awareness and Preventive Behaviours

  Fortunato Cassalia, Christian Ciolfi, Filippo Scolaro, Andrea Danese, Anna Lunardon, Francesca Caroppo, Anna Belloni Fortina

  adv15341

• Melanoma Prognosis and Associated Risk Factors: A Retrospective Cohort Study Using Semantic Map Analysis

  Simone Cazzaniga, Carole Anouk Zahn, Seyed Morteza Seyed Jafari, Robert Emil Hunger

  adv9591

• How Does a Convolutional Neural Network Trained to Differentiate between Invasive Melanoma and Melanoma In situ Generalize when Assessing Dysplastic Naevi?

  Martin Gillstedt, Klara Segerholm, Ludwig Mannius, John Paoli, Sam Polesie

  adv00891

• Risk of Non-cutaneous Cancers in Individuals with Basal Cell Carcinoma: A Population-based Cohort Study

  Hanna Kuru, Jari Jokelainen, Kaisa Tasanen, Laura Huilaja

  adv00826

• Hyperspectral Imaging for Non-invasive Diagnostics of Melanocytic Lesions

  John Paoli, Ilkka Pölönen, Mari Salmivuori, Janne Räsänen, Oscar Zaar, Sam Polesie, Sari Koskenmies, Sari Pitkänen, Meri Övermark, Kirsi Isoherranen, Susanna Juteau, Annamari Ranki, Mari Grönroos, Noora Neittaanmäki

  adv00815
• 

  Evaluation of Melanoma Thickness with Clinical Close-up and Dermoscopic Images Using a Convolutional Neural Network

  Martin Gillstedt, Ludwig Mannius, John Paoli, Johan Dahlén Gyllencreutz, Julia Fougelberg, Eva Johansson Backman, Jenna Pakka, Oscar Zaar, Sam Polesie

  adv00790
• 

  Ability to Predict Melanoma Within 5 Years Using Registry Data and a Convolutional Neural Network: A Proof of Concept Study

  Martin Gillstedt, Sam Polesie

  adv00750

• Hidradenitis Suppurativa International Online Community: Patient Characteristics and a Novel Model of Treatment Effectiveness

  Jen Barak-Levitt, Ron Held, Yossi Synett, Noa Kremer, Emmilia Hodak, Shany Sherman

  adv00686

• Deep Learning-based Trichoscopic Image Analysis and Quantitative Model for Predicting Basic and Specific Classification in Male Androgenetic Alopecia

  Meng Gao, Yue Wang, Haipeng Xu, Congcong Xu, Xianhong Yang, Jin Nie, Ziye Zhang, Zhixuan Li, Wei Hou, Yiqun Jiang

  adv00635