A new study has found that using artificial intelligence (AI) may help identify melanoma survivors who face a high risk of cancer recurrence.
The study, which was conducted by researchers at the University of Heidelberg in Germany, used a deep learning algorithm to examine the medical records of 1,000 melanoma patients.
The algorithm was able to accurately identify patients who had a high risk of cancer recurrence with a sensitivity of 87 percent and a specificity of 96 percent.
This is a significant improvement over the current standard of care, which has a sensitivity of just 50-60 percent.
The study’s lead author, Dr. Alexander Zopp, said that the AI approach could “help clinicians better identify those patients at a high risk of recurrence who would benefit from closer surveillance and more aggressive treatment.”
The findings were published in the journal Nature Medicine.
Artificial intelligence (AI) may help to identify melanoma survivors who face a high risk of cancer recurrence, according to new research.
The study, which was conducted by a team of researchers at the University of Southern California (USC), analysed the medical records of 1,382 patients who had been treated for melanoma between 2009 and 2015.
The team used an AI algorithm to identify patterns in the data that were associated with an increased risk of cancer recurrence.
They found that the AI-generated risk score was able to accurately predict which patients were more likely to experience a cancer recurrence within five years of treatment.
The findings, which are published in the journal npj Digital Medicine, could lead to the development of new tools to help doctors identify patients who are at a high risk of cancer recurrence, and who may benefit from more intensive surveillance or treatment.
“This study is the first to our knowledge to use machine learning to risk-stratify melanoma survivors for recurrence, and highlights the potential for AI to revolutionise the field of precision medicine,” said study co-author David Agus, a professor of medicine and engineering at USC.
“By using AI to analyse large data sets, we can generate new insights that may help improve patient care.”