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AI-driven blood analysis may be the key to unlocking cancer’s secrets

2025-02-23 03:30:09 英文原文

Affordable cancer screening may be available to Hong Kong residents within three years, as advances in artificial intelligence (AI) make the early detection of malignant tumours easier and faster, according to the creator of a pioneering prenatal test for Down syndrome.

AI helps researchers recognise patterns in the gene fragments they find in blood plasma, sparking a revolution in the field of epigenetics, or the study of non-mutation behavioural effects on genes, said Professor Dennis Lo Yuk-ming.

The AI-powered method enables researchers to decipher epigenetic signals from DNA samples without the damaging effects of the chemical treatment that destroys 90 per cent of the genetic material, he said.

“My team members and I were asking: is it possible to use some of the AI methods developed for facial recognition [to help us] see things we cannot see?” Lo said during a January 7 interview with the Post. “As it turned out, it is.”

Professor Allen Chan Kwan-chee (left) and Professor Dennis Lo Yuk-ming (right) of the Chinese University of Hong Kong on 10 August 2017. Photo: Dickson Lee

Professor Allen Chan Kwan-chee (left) and Professor Dennis Lo Yuk-ming (right) of the Chinese University of Hong Kong on 10 August 2017. Photo: Dickson Lee

Lo’s team at the Centre for Novostics at the Hong Kong Science and Technology Park developed an in-house AI system based on the Convolutional Neural Network, a deep learning model that was designed mainly for image recognition. With advances in generative AI tools such as ChatGPT, the company also incorporated the transformer neural network architecture into the system, he said.

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摘要

Advances in artificial intelligence could make affordable cancer screening available to Hong Kong residents within three years. Professor Dennis Lo Yuk-ming, creator of a pioneering prenatal test for Down syndrome, says AI helps recognize patterns in gene fragments found in blood plasma, revolutionizing epigenetics. His team at the Centre for Novostics developed an AI system using Convolutional Neural Networks and transformer neural network architecture to detect epigenetic signals from DNA samples without damaging them.