Sam Polesie

Adjunct Senior Lecturer

Department of Dermatology and Venereology

Mail

sam.polesie@gu.se

Visiting address

Gröna stråket 16 Pl 2 SU/Sahlgrensk

41345 Göteborg

Postal address

Sahlgrenska Universitetssjukhuset

41345 Göteborg

About Sam Polesie

Sam Polesie is a consultant dermatologist, Associate Professor (Docent) in Dermatology and Venereology, Adjunct Senior Lecturer at the University of Gothenburg, and research group leader at the Center for Digital Health, Sahlgrenska University Hospital. He obtained his PhD in Medical Science in 2019 with a thesis entitled Methotrexate and Risk of Cutaneous Melanoma.

He has a strong commitment to undergraduate medical education. Since autumn 2023, he has served as Course Leader in Dermatology and Venereology, and since autumn 2025, as Examiner for semester 9 (LPG009) of the Medical Degree Program at the University of Gothenburg, with overall responsibility for examinations, assessment, and grading.

Research focus area

His primary research interests are skin cancer epidemiology, artificial intelligence (AI), and the development and clinical evaluation of machine learning algorithms for skin cancer diagnosis and risk prediction. His overarching aim is to improve diagnostic precision, support clinical decision-making, and contribute to more personalized and resource-efficient healthcare.

His early research focused on the association between immunomodulatory treatments and skin cancer. In a nationwide Danish study including more than 176,000 patients with skin cancer, methotrexate exposure was associated with an increased risk of basal cell carcinoma, squamous cell carcinoma, and melanoma (Polesie et al. British Journal of Cancer, 2023). This observational study attracted considerable scientific and public attention, reaching the 99th percentile according to Altmetric.

In recent years, his research has increasingly focused on AI-based skin cancer diagnostics. In an international study involving 438 participants from 63 countries, his research group investigated the ability of dermatologists and machine learning algorithms to assess melanoma thickness using dermoscopic images. The results demonstrated the limitations of human assessment and showed that machine learning achieved performance comparable to aggregated dermatologist assessments (Polesie et al. Journal of the European Academy of Dermatology and Venereology, 2022). This study also reached the 99th percentile according to Altmetric.

Another important research area is the use of AI for preoperative assessment of keratinocyte carcinomas. His research group has demonstrated that machine learning algorithms can achieve performance comparable to dermatologists when assessing histopathological risk characteristics of squamous cell carcinoma (Liang et al. JAAD International, 2025) and basal cell carcinoma (Liang et al. JAAD International, 2026).

He also conducts research on predicting future skin cancer risk using nationwide healthcare registry data. In collaboration with Chalmers University of Technology, his research group developed machine learning models based on data from more than six million Swedish adults to predict melanoma risk (Gillstedt et al. Acta Dermato-Venereologica, 2026).

A further research interest is scientific transparency and the sharing of clinical images in dermatological research. In a systematic review of randomized controlled trials involving nearly 63,000 patients with psoriasis, his research demonstrated that published clinical images represented only 0.1% of participants (Polesie et al. Journal of Dermatological Treatment, 2023).

Current research and academic activities

His current research focuses on the clinical validation and implementation of AI-based diagnostic tools. He is the principal investigator of a prospective clinical trial evaluating AI-based assessment of melanoma thickness (ClinicalTrials.gov, NCT06788665). He also leads projects investigating preoperative risk assessment of keratinocyte carcinomas and machine learning-based prediction of skin cancer risk, in collaboration with Chalmers University of Technology and other national and international research partners.

He is actively engaged in doctoral supervision, scientific peer review, and academic leadership. He serves as an Editorial Board Member of the Journal of the American Academy of Dermatology (JAAD) and as Section Editor of Acta Dermato-Venereologica.

Beyond his clinical and research activities, he has a particular interest in medical ethics, which he teaches in the Medical Program. He also contributes to public discourse on ethical issues related to medicine, healthcare, and emerging technologies.

Research in the media

His research has been featured in several press releases and research news articles from the University of Gothenburg:

2026: AI hittar tidiga riskmönster för hudcancer

2025: Equivalent outcomes when AI and dermatologists assess skin cancers

2024: AI-baserad app kan hjälpa läkare hitta hudmelanom

2023: Patienter med psoriasis syns sällan i publicerade studier

2023: Läkemedlet metotrexat kopplas till förhöjd risk för hudcancer

2022: Lika svårt för algoritmer och hudläkare bedöma tjocklek på melanom

2022: Algoritmer på registerdata som hjälp för tidig upptäckt av hudcancer

His research has also received attention in national and international media, including Läkartidningen, Oncology Times, MedPage Today, Swedish Radio, and SVT.