AI Can Identify Melanoma Risk Years Before Diagnosis, Swedish Study Finds
Researchers from the University of Gothenburg in Sweden have developed an artificial intelligence model capable of identifying individuals at high risk of developing melanoma up to five years before diagnosis. By analyzing clinical data from approximately six million Swedish adults between 2005 and 2014, the study utilized existing healthcare registry information, including medication history, previous diagnoses, and sociodemographic factors. The advanced AI model successfully distinguished future melanoma patients from non-patients in about 73% of cases, significantly outperforming models relying solely on age and gender. The research identified small, high-risk groups with a 33% probability of developing the disease within five years. This breakthrough highlights the potential for using routine health data to enable selective screening, allowing clinicians to prioritize follow-ups for those most at risk. Such targeted approaches could lead to earlier detection, improved survival rates, and more efficient use of healthcare resources. However, the authors emphasize that further research and policy decisions are necessary before integrating this method into standard medical practice. The findings underscore the growing role of AI in personalized risk assessment and preventive healthcare strategies for skin cancer.
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AI Can Identify Melanoma Risk Years Before Diagnosis, Swedish Study Finds
Researchers from the University of Gothenburg in Sweden have developed an artificial intelligence model capable of identifying individuals at high risk of developing melanoma up to five years before diagnosis. By analyzing clinical data from approximately six million Swedish adults between 2005 and 2014, the study utilized existing healthcare registry information, including medication history, previous diagnoses, and sociodemographic factors. The advanced AI model successfully distinguished future melanoma patients from non-patients in about 73% of cases, significantly outperforming models relying solely on age and gender. The research identified small, high-risk groups with a 33% probability of developing the disease within five years. This breakthrough highlights the potential for using routine health data to enable selective screening, allowing clinicians to prioritize follow-ups for those most at risk. Such targeted approaches could lead to earlier detection, improved survival rates, and more efficient use of healthcare resources. However, the authors emphasize that further research and policy decisions are necessary before integrating this method into standard medical practice. The findings underscore the growing role of AI in personalized risk assessment and preventive healthcare strategies for skin cancer.
euronews