Doctor Can Now Detect Breast Cancer Using This Software Powered By AI

It was not until the introduction of mammograms that the death rates of people with breast cancer decreased by 27 percent in a period of two decades. However, the process of finding cancerous tissues by mammograms is not as easy as it seems, the reason behind this particular matter is because the breast tissues also have the same white color as the cancerous ones on a common X-rays.

However, this problem will soon be solved because radiographers and scientists have been applying the advancement of AI to pinpoint cancerous tissues, which could help boost the breast screening’s performance. Volpara Health Technologies’ base in New Zealand is developing software that has the ability of automatically and objectively assessing mammograms – basically the X-rays of breast tissue –spotting the images that may need further follow-up review by doctors or radiographers.

How This Technology Helps Detect Early Stages Of Cancer

It is said that the technologies above can detect the earliest stages of cancer, which can create the best chance for the patient with breast cancer to have a successful treatment, and again help them reduce the rate of “interval cancers” that could emerge between the screening process. This software exploits the power of Microsoft’s suite of AI tools, Power BI.

The system’s algorithm first analyses the X-rays of breast tissues for the breast density, the output data taken from the analysis can be used to flag the images that may need further inspection. The system had gone through a massive number of mammogram X-rays images in its training.

The Uses Of The Software Around The World

Dr. Ralph Highnam – founder of the Volpara Health Technologies – wanted to use Artificial Intelligence as a mean to help doctors and radiographers alike with overcoming the hardships during breast cancer detection. With only ten years of working, the Volpara has currently been used in many countries, which include America, Australia, Japan and of course, New Zealand.

The corporation is currently and going to further develop its technologies with the hope that the same advancement can be seen with AI technologies to create tools that can pinpoint cancer growth at the moment of breast screening.

The introduction of digital mammograms was dated back in the 90s, the patient must first stand in front of the X-rays machine, after that the patient will have to have their breast put in between plates of clear plastic. Then the X-rays will be completed, and the same process goes for the other breast.

Frequent Evaluations Are Recommended

The results X-rays will be immediately assessed for clarity by X-ray technicians. However, the images have to be examined by radiologists or doctors before official results get to the hands of the patient. Although mammogram only takes a short amount of time, it is a troublesome procedure, in which the patient can experience pain.

According to most health organizations, women from the age of 50 to 70 should have a mammogram every year because a patient’s previous mammogram is crucial data for the doctors to analyze and compare the alterations in the breast tissue.

Other Processes Will Also Embrace AI

There is no denying that AI is being used more and more in the field of the health industry, which is a useful tool to help professional assess scans and doctors. And another research has emerged involving the use of AI to improve the rate of success in IVF (In Vitro Fertilization) treatments.

The IVF first successful case was in 1977, which since then has been aiding people to improve their reproductive disadvantages. Despite the advancement of technologies, there still exist some aspects of the IVF that are currently considered relatively faulty and time-consuming.

One of these aspects is the process known by the name “grading,” which requires an examination of embryos by an embryologist. The embryos will be analyzed under a microscope to check their morphological features and assign a quality score.

Fragmented, and fractured cells will have a poor score while even, and round numbers of cells will have a higher score. An algorithm has now been available for better grading the embryos, which is said to do a better job than its embryologist counterpart.

A Google algorithm for deep learning was trained to grade the embryos as either poor, fair, or sound, and based on the grading that the embryos would be implanted successfully.

AI has such potential in medical uses, and there is no doubt that it will develop in the future.