Artificial Intelligence technologies assisting health specialists’ skills to bring the promise of an era in which monotonous and time-intensive tasks in healthcare can be automated and executed (either entirely or in part) by AI systems. As automation progressively facilitates the delivery of health care, physicians can now provide more civilized patient care. The use of AI to secure quality delivery is important to combat the diseases and there is no doubt that the next decade will see a growing line of AI applications across healthcare. Despite major advances that have taken place in treatment and diagnosis, cancer remains the most deadly disease across the globe. The most dangerous cancer which is very difficult to diagnose is breast cancer. How healthcare providers are using Artificial Intelligence in breast cancer treatment?
About one in ten cancer patients are misdiagnosed as not cancerous, meaning that a patient can lose proper treatment time. On the other hand, the more mammograms a woman has, the more likely she will see a false-positive result. After 10 years of annual mammograms, abruptly two out of three patients who do not have cancer will be told that they do and be subjected to an invasive intervention, most likely a biopsy. Digital mammography has various benefits compared to screen-film mammography and the chief among them is the simpler workflow. It helps in rapid identification and therefore the patient gets time for treatment.
Breast ultrasound elastography
Breast ultrasound elastography is an evolving imaging technique that generates information about a possible breast abscess by assessing its stiffness in a non-invasive way. Using more accurate information about the elements of a cancerous versus non-cancerous breast abscess, this methodology has demonstrated more accuracy compared to the traditional modes of imaging.
Breast Cancer Detection
If breast cancer is caught early it has a maximum of 5 years of survival rates, but once it starts spreading, the rate of survival starts reducing. There are detection methods that have high false positives and negative rates which leads to delayed treatment for patients with breast cancer. AI-based algorithms in such situations can help reduce false positives and negatives in the diagnosis of breast cancer. The algorithms work hand in hand with doctors, drawing attention to regions on a mammogram that looks like they could contain tumors or evidence of malevolent tissue. These Artificial Intelligence -based detection methods can lead to quicker treatment for the patients that need it.
Implementation of AI in therapy
Immunotherapy is a treatment for all types of cancer that uses drugs to uplift the immune system of the human which will help it to fight off malevolent cells. Unlike other therapies like chemo and radiation, this method has fewer side effects and is highly effective. However, not all patients react the same, and there’s no way of knowing whether immunotherapy will work or not. To make this possible AI algorithm in combination with CT scans can be used to recognize patients who are most likely to react well to immunotherapy. This enables doctors to provide identified patients with immunotherapy treatment.
Radiation therapy is one of the most productive treatments available for many different types of cancer, mainly breast cancer. However, it is hugely hard on the body, and it is often hard to assume how patients will respond.
But AI is successfully used by doctors to plan where to target radiation therapy and predict how well a patient is likely to react to the effects. Artificial Intelligence enables doctors to better plan radiotherapy treatment for breast cancer patients.