A study on the whole adult population of Sweden via analysing registry data on age, sex, diagnosis and socioeconomic status found that artificial intelligence (AI) models could predict rates of melanoma with almost 73% accuracy.
A collaborative study between the University of Gothenburg and Chalmers University of Technology applied analytical AI models to a data pool containing over six million Swedish adults.
Using registry data of 6,036,186 individuals and informed by demographic factors such as age and sex, the AI was able to identify small groups at high risk for developing melanoma with a high level of accuracy.
The data focused on over 38,000 cancer diagnoses
When only age and sex were factored into the registry data, the AI models were able to distinguish people who would later develop melanoma with roughly 64% accuracy. A more advanced model informed with comprehensive demographic data managed to increase accuracy to 73%.
When informed with diagnoses, medications and sociodemographic data, the models could identify smaller high-risk groups, who faced a 33% risk of developing melanoma within five years.
Of the 6,036,186 individuals studied through the registry data, 38,582 (0.64%) were diagnosed with melanoma over the course of the five-year study.
Making cancer screening strategies much more efficient
“Our study shows that data which is already available within healthcare systems can be used to identify individuals at higher risk of melanoma,” says Martin Gillstedt, a doctoral student at the University of Gothenburg’s Sahlgrenska Academy and a statistician at Sahlgrenska University Hospital’s Department of Dermatology and Venereology.
“This is not a form of decision support that is currently available in routine healthcare, but our results give a clear signal that registry data can be used more strategically in the future.”
Published in Acta Dermato-Venereologica, the study was led by Sam Polesie, Associate Professor of Dermatology and Venereology at the University of Gothenburg and a dermatologist at Sahlgrenska University Hospital:
“Our analyses suggest that selective screening of small, high-risk groups could lead to both more accurate monitoring and more efficient use of healthcare resources. This would involve bringing population data into precision medicine and supplementing clinical assessments.”
The use of AI models trained on registry data is still developing and more research is needed, warns the paper. But early results, such as the finding of this study suggest that AI could make future screening strategies for skin cancer more effective.
Team Health Accessible
Health & Wellness Editorial Team
HealthAccessible editorial team delivers trusted, accessible, and evidence-based health information for everyone.
