Artificial Intelligence in the Battle Against Breast Cancer
Breast Cancer Awareness Month, which has been held every October for the past four decades, has helped to raise awareness and sensitization about the world’s most common cancer condition (which claims over three-quarters of a million lives each year).
Regardless of documented examples dating back to ancient Egypt, breast cancer was deemed a “unspeakable” illness in which women were expected to endure in quiet and “dignity. “Until recently, this stigma existed deep in the abyss, fueled by academic illiteracy and a lack of energy as a relatively unknown condition. For most of the last century, a woman with breast cancer would be offered radiation therapy and/or surgery (typically extensive surgery), leaving her scarred for little benefit while other cancers were being treated.
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Breast cancer mortality rarely altered from the 1930s to the 1970s until a well-coordinated movement by feminist and women’s liberation groups elevated the study and treatment of breast cancer to its appropriate place in mainly male-dominated hospitals and research institutions. Now there’s something to rejoice over: Thanks to improved medications, cutting-edge screening procedures, and more subtle and effective surgery, the chance of surviving the next 10 years after being diagnosed with breast cancer in the 1970s has nearly quadrupled to around 40%.
The emphasis on early diagnosis has been credited with this shift, as cancer is easily treated when detected early. Artificial intelligence (AI) has/will play an increasingly important role in detecting breast cancer as a result of this. The National Health Service (NHS) in the United Kingdom said this year that it would do research into how AI may be used to screen for breast cancer. While AI was designed to complement, not replace, human doctors, it might help alleviate a radiographer shortage — 2,000 more are needed to clear the NHS’ scan backlog generated by the pandemic. AI is also being used by startups to address the shortfall.
The use of AI to screen half a million women for breast cancer is part of Kheiron Medical Technologies’ stated objective. Spain’s Blue Box is developing a device that can identify breast cancer from urine samples, while India’s Niramai is developing a low-cost instrument that could assist screen huge numbers of women in rural and semi-urban regions. Identifying individuals at high risk of recurrence is one of the most important approaches to improve results. After their initial therapy, about one out of every ten breast cancer patients will relapse, lowering their chances of survival. Early detection of breast cancer has been difficult in the past, but a team working with Gustave Roussy, a French cancer hospital, has developed an AI tool that can identify 8 out of 10 women who are at high risk of recurrence. People can obtain the treatment they need sooner, and AI can save lower-risk patients from having to go to the doctor as often. Pharmaceutical companies, on the other hand, are speeding up breast cancer medication studies by enlisting more high-risk patients.
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Patient data privacy is one of the reasons that slows down research, which is understandable given the circumstances. Hospitals are wary of transferring data off-site, and no pharmaceutical firm wants to share sensitive information with competitors; however, AI is assisting in the resolution of these challenges, allowing for the creation of new treatments to be faster, safer, and less expensive.
Through the use of Federated learning, a revolutionary form of AI that trains on data from various institutions without the data leaving the jurisdiction of the hospitals, researchers throughout Europe were given access to critical, but previously inaccessible, data. Artificial intelligence will also be utilised to better understand why the most aggressive kinds of breast cancer are resistant to particular medications, assisting in the development of new drugs that distinguish between healthy and tumour cells more effectively than chemotherapy.
With AI’s influence growing, it’s important to remember that improving outcomes is a recognition that healthcare is fundamentally a human endeavour, as no algorithm or machine could ever console a patient in their darkest moments, let alone instil and inspire the resilience that every patient requires to overcome their disease. For the millions who are affected by breast cancer, be assured that the disease is no longer “unspeakable,” but rather something that, with the help of AI and other medical technology, we will be able to overcome and decrease its impact in the near future. Breast cancer may not be completely eradicated, but with faster diagnosis thanks to AI, it sets the stage for rapid treatment development. In a few decades, breast cancer awareness may be obsolete since everyone will know how to avoid and treat it.