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AI Spots Early Melanoma Risk Using Routine Health Data, Study Finds

A new study from Sweden demonstrates that artificial intelligence can analyze routinely collected health registry data to identify individuals at a higher risk of developing melanoma. The research, involving over 6 million adults, found that an advanced AI model could distinguish future melanoma patients with about 73% accuracy. By combining diagnoses, medication use, and socioeconomic data, the AI pinpointed small, high-risk groups where the chance of developing the cancer within five years was around 33%. The researchers suggest this method could lead to more precise and efficient screening strategies, though further policy decisions are needed before clinical implementation.

Key Points: AI Identifies Early Skin Cancer Risk from Health Registry Data

  • AI analyzed registry data of 6 million Swedes
  • Identified high-risk groups with 33% 5-year melanoma risk
  • Advanced model achieved 73% accuracy
  • Enables more efficient, targeted screening
2 min read

AI can spot early risk patterns for skin cancer, finds study

A Swedish study shows AI can analyze routine health data to identify individuals at high risk for melanoma, improving early detection and screening efficiency.

"Our study shows that data which is already available within healthcare systems can be used to identify individuals at higher risk of melanoma. - Martin Gillstedt"

New Delhi, April 15

Artificial intelligence can identify early risk pattern among individuals at higher risk of melanoma, a new study showed on Wednesday.

The study was based on registry data that is routinely collected on the whole of Sweden's adult population.

The analysed data included age, sex, diagnoses, use of medications and socioeconomic status.

Of the 6,036,186 individuals included, 38,582 (0.64 per cent) developed melanoma during the five years of the study.

"Our study shows that data which is already available within healthcare systems can be used to identify individuals at higher risk of melanoma," said Martin Gillstedt, a doctoral student at the University of Gothenburg's Sahlgrenska Academy.

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, said Gillstedt, a statistician at Sahlgrenska University Hospital's Department of Dermatology and Venereology.

When the researchers compared different AI models, the differences became clear.

The most advanced model was able to distinguish individuals who subsequently developed melanoma from those who did not in about 73 per cent of cases, compared with about 64 per cent when only age and sex were used.

The combination of diagnoses, medication and sociodemographic data made it possible to identify small, high-risk groups for whom the risk of developing melanoma within five years was around 33 per cent.

"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," said Sam Polesie, Associate Professor of Dermatology and Venereology at the University of Gothenburg.

More research and policy decisions are needed before the method can be introduced in healthcare. However, the results show that AI models trained on large amounts of registry data can become an important source of support for more personalized risk assessments and future screening strategies for melanoma.

- IANS

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Reader Comments

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Rohit P
The 73% accuracy is promising, but we must be careful. AI is a tool, not a doctor. In our context, we need to ensure such tech doesn't widen the urban-rural healthcare gap. Will it be affordable and accessible in primary health centres?
A
Arjun K
Very interesting study. The part about identifying small high-risk groups with a 33% chance is key. It means resources can be focused. Hope Indian researchers and institutions like AIIMS are working on similar models with our population data.
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Sarah B
As someone who spends a lot of time outdoors, this gives me hope. But the article says more policy decisions are needed. Data privacy is a huge concern. Who gets access to our medical history? Strong safeguards are a must before implementation.
V
Vikram M
Good step for preventive healthcare. However, we need to address the basics first. Awareness about sun protection in India is very low. Can AI also help run awareness campaigns targeted at high-risk professions like farmers and construction workers?
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Karthik V
The potential is immense, but the study is on Swedish data. Indian skin types, genetics, and environmental factors are different. We need large-scale, India-specific research to make this truly effective here. Jai Hind to our scientists working on this!

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