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9 Articles
One study has developed about 500 machine learning models aimed at estimating the risk of 20 types of cancer.
Madrid, Oct 26 (EFE).- Artificial intelligence and machine learning models based on health data that are routinely collected have demonstrated their potential to identify people at higher risk of developing several of the most common types of cancer. This is evidenced by a study that has been presented in [...] The entry AI and machine learning would help detect people at risk of cancer was first published in HolaNews.
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Machine learning models based on routinely collected health data - such as blood tests, medical history, genetic and metabolomic data, or lifestyle factors - could help identify people at higher risk of developing several of the most common types of cancer, according to an international study presented at the European Society of Medical Oncology Congress (ESMO 2026).
The possibility of identifying a person at higher risk of developing cancer years before receiving a diagnosis could open up new opportunities for prevention and early detection. And it would not necessarily take extraordinary tests to achieve this. Usual blood tests, medical history and certain life habits could contain information [...] The entry The AI could anticipate the risk of developing cancer through routine blood tests appears first in…
The Congress of the European Society of Oncological Medicine (ESMO 2026) takes place this year from 23 to 27 in Madrid. One of the studies that have been presented underlines how machine learning models based on routinely collected health data could help identify people at greatest risk of developing 20 of the most common types of cancer. The post Machine learning would help identify people with the most cancer risk was first published in Health…
An international study presented at the ESMO 2026 Congress presented particularly promising results for lung, esophagus and liver cancers.
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