AI tool finds cancer signs missed by doctors

Ryan Daws is a senior editor at TechForge Media with over a decade of experience in crafting compelling narratives and making complex topics accessible. His articles and interviews with industry leaders have earned him recognition as a key influencer by organisations like Onalytica. Under his leadership, publications have been praised by analyst firms such as Forrester for their excellence and performance. Connect with him on X (@gadget_ry) or Mastodon (

An AI tool has proven capable of detecting signs of cancer that were overlooked by human radiologists.

The AI tool, called Mia, was piloted alongside NHS clinicians in the UK and analysed the mammograms of over 10,000 women. 

Most of the participants were cancer-free, but the AI successfully flagged all of those with symptoms of breast cancer—as well as an additional 11 cases that the doctors failed to identify. Of the 10,889 women who participated in the trial, only 81 chose not to have their scans reviewed by the AI system.

The AI tool was trained on a dataset of over 6,000 previous breast cancer cases to learn the subtle patterns and imaging biomarkers associated with malignant tumours. When evaluated on the new cases, it correctly predicted the presence of cancer with 81.6 percent accuracy and correctly ruled it out 72.9 percent of the time.

Breast cancer is the most common cancer in women worldwide, with two million new cases diagnosed annually. While survival rates have improved with earlier detection and better treatments, many patients still experience severe side effects like lymphoedema after surgery and radiotherapy.

Researchers are now developing the AI system further to predict a patient’s risk of such side effects up to three years after treatment. This could allow doctors to personalise care with alternative treatments or additional supportive measures for high-risk patients.

The research team plans to enrol 780 breast cancer patients in a clinical trial called Pre-Act to prospectively validate the AI risk prediction model over a two-year follow-up period. The long-term goal is an AI system that can comprehensively evaluate a patient’s prognosis and treatment needs.

(Photo by Angiola Harry)

See also: NVIDIA unveils Blackwell architecture to power next GenAI wave 

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

Tags: , , , , , , , ,

View Comments
Leave a comment

Leave a Reply