- News Karnataka school sedition case challenged in SC
- Movies Box Office Collection Report: Shubh Mangal Zyada Saavdhan VS Bhoot Part One: The Haunted Ship
- Technology Redmi 8A Dual Will Be Available Via Open Sale
- Sports FIH Hockey Pro League: Fighting India go down to Australia
- Education Top 20 Universities In Emerging Economies University Rankings 2020
- Finance Gold Hits 7-Year High As Caronavirus Fears Persist
- Automobiles 2020 Hyundai Tucson Bookings Commences — All You Need To Know
- Travel Top 6 Places To Visit In India To Observe Maha Shivratri!
Breast cancer, the second most common cancer in women, has been a matter of grave concern to the scientists and the patients alike for decades. However, according to a new study conducted by a group of UK researchers recently, the state-of-the-art AI technology has been able to detect patterns in breast cancer. As a result, they have distinguished five new types of breast cancer, each matching to different treatments.
The study published in the NPJ Breast Cancer Journal, has witnessed the use of AI and machine learning (ML) in gene sequences and molecular data from breast tumours. This new technology has uncovered significant differences among types of breast cancers that had earlier been presumed as one type.
According to the team at the London's Institute of cancer Research, who performed the research, two of the new found types are more likely to respond to the immunotherapy than the others, while one type of this disease is more prone to be treated with the help of tamoxifen.
"Our study has shown that AI can recognise patterns in breast cancer that are beyond the limit of the human eye, and to point us to new avenues of treatment among those who have stopped responding to standard hormone therapies," mentioned the study leader and author, Dr Anguraj Sadanandam.
The same team previously used AI algorithm to recognise five different types of bowel cancer. This time, they applied the AI-trained computer software to a vast array of data available on the genetics, molecular and cellular make-up of primary 'luminar A' breast tumours and even the survival rate of patients affected by this condition.
After the remarkable performance of this newly trained AI software, the researchers are now planning to develop tests for cancer types that will aid in creating personalised treatment therapy for patients. They aim to apply the same algorithm to various types of cancer in order to reveal how each new type reacts to different treatments.
"AI has the capacity to be used much more widely, and we think we will be able to apply this technique across all cancers, even opening up new possibilities for treatment in cancers that are currently without successful options," added Dr Sadanandam.
The study also mentioned that most cases of breast cancers develop in the inner cells that line the mammary ducts and are "fed" by the hormones oestrogen or progesterone.
Though the recent developments of this study do not challenge the overall classification of breast cancer, but they disclose a plethora of additional differences within the current sub-divisions of the disease, explained the researchers.
"Among the exciting implications of this research is its ability to pick out women who might respond well to immunotherapy, even when the broad classification of their cancer would suggest that these treatments wouldn't work for them," explained Dr Maggie Cheang, team leader of the Genomic Analysis Clinical Trials Team at The Institute of Cancer Research, London.
It will be fascinating to see how this new-age technology transforms the future of cancer treatment.