How Artificial Intelligence Is Used To Fight Breast Cancer

The sensitization and awareness of the most rife cancer ailment in the world (one that takes almost three-quarters of a million lives every year) has been raised through the help of Breast Cancer Awareness Month, an event that has been holding every October in the last four decades.

Breast cancer, considered an “unspeakable” condition where women were expected to suffer in silence and “dignity”, regardless of recorded cases stretching back to ancient Egypt.

Until recently, this stigma was in the abyss and it was greatly powered academic ignorance, with lacking vigour as a relatively unstudied disease. For most of the last century, radiation therapy and/or surgery (often radical surgery) would be offered to a woman suffering from breast cancer, leaving them disfigured for little benefit, while the treatment of other cancer progressed.

Until a well coordinated effort by feminist and women’s liberation groups exalted the study and treatment of breast cancer to its rightful position in heavily male-dominated hospitals and research institutions, breast cancer mortality barely changed from the 1930s to the 1970s.

Now, there is something to be happy for:  In appreciation to new drugs, cutting – edge screening methods, and more subtle and effective surgery, the probability of roughly 40% chance of surviving the next 10 years after been diagnosed with breast cancer in the 1970s has almost doubled.

The credit to this transformation has been emphasis on early diagnosis, as Cancer is easily treated when diagnosed early. It is in cognizance of this that Artificial intelligence (AI) has/will be playing an increasingly critical role in identifying breast cancer.

A study of how AI could screen for breast cancer was announced by Britain’s National Health Service (NHS) this year. While AI was intended to augment, not replace, human doctors, the technology would help to mitigate a shortage of radiographers – 2,000 more are needed to clear the NHS’ backlog in scans caused by the pandemic. Startups are also using AI to tackle this shortage.

Part of Britain’s Kheiron Medical Technologies avowed mission is the use of AI to screen half a million women for breast cancer.  A device that has the capacity to detect breast cancer from urine samples is under construction by Spain’s the Blue Box, while India’s Niramai is working on a low cost tool that could help screen large numbers of women in rural and semi-urban areas.

One of the essential ways to improving outcomes is identifying patients at high risk of recurring. About one in ten breast cancer patients will fall back after their initial treatment, in the process decreasing their chance of survival.

Detecting breast cancer early has been historically difficult, but a team working with Gustave Roussy, a French cancer hospital, has developed an AI tool that can spot 8 in 10 patients at high risk of recurring. Patients can get the treatment they need earlier on while also sparing lower-risk patients from frequent, unsettling check-ups through AI. Meanwhile, pharmaceutical companies accelerate breast cancer drug trials by recruiting high-risk patients faster.

One of the factors that impedes rapid research is Patient data privacy, even though is understandable with the situations involved. Hospitals are careful about sending data off-sites, and no pharmaceutical company wants to share valuable data with competitors, but AI is however helping to solve these issues, allowing for the quicker, safer and cheaper development of new treatments.

Researchers across Europe were given access to essential, yet previous inaccessible, data, through the use of Federated learning, a novel form of AI that trains on data from multiple institutions without the data leaving the purview of the hospitals.

Artificial Intelligence will also be used to widen our understanding of why the most aggressive forms of breast cancer are resistant to certain drugs, helping to develop new drugs that distinguishes between healthy and tumour cells better than chemotherapy.

With AI’s influence on the increase, it is expedient to note that improving outcomes is a recognition that healthcare is a fundamentally human strive, as no algorithm or machine could ever comfort a patient in their darkest moments nor instil and inspire the resilience that every patient needs in order to defeat their disease.

For the millions suffering from breast cancer, rest assured that the ailment is no longer ‘unspeakable’ but something we can with the use of AI and other medical technologies surmount and reduce its effect in the soon future. Breast cancer may not be totally eradicated, but with quicker diagnosis with the use of AI, that sets the tone for rapid development of treatments, in few decades to come, awareness for breast cancer may no longer be needed as everyone might have be availed on what to do to prevent and treat it.