As with any life threatening disease, early detection is critical to the successful treatment of cancer. The global mortality rate for the killer disease was as high as 14.4% in 2018, according to the World Health Organization. One of the key reasons for this is the alarmingly high rate of misdiagnosis or faulty reporting. Moreover, mammograms – the most common diagnostic tool for investigating breast cancer- also expose patients to high levels of radiation. The search for safer, more accurate alternatives has led to the rapid development of Artificial Intelligence (AI) based diagnostics techniques.
Faster and more accurate results
The role of incorrect pathology reports in the classification of cancerous lung tissue cannot be discounted. In fact, up to 22% of all such cases have been attributed to wrong blood or tissue samples in a recent study. While clinical factors are often to blame, human error does contribute to delayed diagnoses that can double the cost of treatment for patients in some cases. This is an area where AI-based imaging software has shown a lot of promise. For example, AI applications are being used in the US and UK to cross-check and verify the observations of doctors in cases that are particularly challenging.
It could only be a matter of time before AI could replace human doctors in diagnosing and suggesting courses of treatment for cancer patients worldwide. Google’s breast screening AI tool has already developed enough proficiency to identify symptoms of breast cancer accurately 99% per cent of the time.
Lowering the cost of cancer treatment
AI-based tools leverage non-invasive imaging for tracking patient response to the treatment being provided. Traditional Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) often require corroboration with other data for doctors to arrive at a decisive conclusion. This can delay treatment and add to the already substantial costs of treatment for patients. AI can reduce the average duration of hospitalization for patients significantly by analysing changes in the growth of cancer cells and projecting future progression.
The average cost of chemotherapy for breast cancer hovers around the $9000 mark. This can make it unaffordable for uninsured or underinsured Americans. AI tools make it possible for physicians to remotely examine patients and recommend in-patient treatment only when absolutely necessary- a lifesaver for millions of individuals and families that cannot afford it.
Personalization of treatment
The one size fits all approach is not very efficient when it comes to treating breast cancer or any condition for that matter. Patients have different levels of tolerance to chemotherapy. By tracking biomarkers, AI tools can help doctors customize radiation dosages to individual needs, greatly improving recovery times and the overall patient experience. Specialist hospitals like the Cleveland Clinic are already using AI to assess risk factors and reduce the toxic side effects of chemotherapy for patients.
AI applications can help doctors assess and treat breast cancer patients more effectively, allowing patients to live healthier, happier lives than ever before. The 2020s are sure to be an exciting time for AI-enabled breast cancer care.