A therapy that would once have been considered a feat of science fiction has reversed aggressive and incurable blood cancers in some patients, doctors report. The treatment involves precisely editing the DNA in white blood cells to transform them into a cancer-fighting living drug. The first girl to be treated, whose story we reported in 2022, is still free of the disease and now plans to become a cancer scientist. Now eight more children and two adults with T-cell acute lymphoblastic leukaemia have been treated, with almost two thirds (64%) of patients in remission. T-cells are supposed to be the body's guardians - seeking out and destroying threats - but in this form of leukaemia, they grow out of control.

"By linking genomic data with machine learning we have been able to predict … The scientists combined this data with an artificial intelligence …

Editor's Note: This is a guest post by Beata Green – Director of London-based HeadChannel Ltd. Her opinions are her own. It is almost impossible to think about something without picturing it. Can you tell what you see when you think about artificial intelligence? Do you picture Alicia Vikander playing Ava in Ex Machina or Arnold Schwarzenegger as the Terminator in your mind?

Machine learning is a subfield of computer science, that grew out of the quest for artificial intelligence. It is so pervasive in today's world that you probably use it often in daily life, without even realising it. Machine learning has given us self-driving cars, effective web search, recommendations that you get when you visit web sites or social media sites, face detection in a digital photo album, stock trading etc. Machine learning enables computers to analyze vast amounts of data and automatically detect patterns and features, or make predictions regarding certain conditions. In a dynamic disease like cancer, gauging and diagnosing such a complex heterogeneity is the biggest challenge. After decades of cancer research, it has become increasingly clear that no two patients' cancers are exactly the same, and even within one person's tumor there is a wild diversity of cells. Accurate and quicker diagnosis is very crucial in rapidly progressing cancers.

Machine learning is a subfield of computer science, that grew out of the quest for artificial intelligence. It is so pervasive in today's world that you probably use it often in daily life, without even realising it. Machine learning has given us self-driving cars, effective web search, recommendations that you get when you visit web sites or social media sites, face detection in a digital photo album, stock trading etc. Machine learning enables computers to analyze vast amounts of data and automatically detect patterns and features, or make predictions regarding certain conditions. In a dynamic disease like cancer, gauging and diagnosing such a complex heterogeneity is the biggest challenge. After decades of cancer research, it has become increasingly clear that no two patients' cancers are exactly the same, and even within one person's tumor there is a wild diversity of cells.

Another example of artificial intelligence doing good is IBM's Watson artificial intelligence engine diagnosing an old woman's leukaemia. The said machine took only 10 minutes to diagnose a rare kind of leukaemia that has been misdiagnosed months earlier. Watson achieved this feat by comparing the patient's genetic changes with 20 million other cancer research papers. This enabled the doctors to perform proper treatment for the patient. In addition to this, the machine also diagnosed another rare type of leukaemia in another patient.