In the age of the Fourth Industrial Revolution, artificial intelligence (AI) is being heralded as one of the major drivers of progress. AI has already revolutionized various industries, from retail to transportation, and it has now set its sights on the medical sector. In recent years, we’ve seen artificial intelligence outperforming human doctors in diagnosing diseases such as breast cancer. This article takes an in-depth look at how AI has been performing in breast cancer diagnosis, and how it could improve the accuracy and cost-effectiveness of medical care.
What is Artificial Intelligence?
Before delving into the particulars of AI-driven breast cancer diagnosis, let’s briefly explore what AI is to better understand its potential. Simply put, AI is the ability of a machine or system to learn and act upon data in a manner akin to the way humans do. AI achieves this through a methodical process known as deep learning – receiving data, processing it, and constructing a response. By training AI-based systems on vast amounts of data, they can develop sophisticated algorithms that enable them to tackle even the most complex tasks, including medical diagnosis.
AI Outperforms Human Doctors
Using advanced AI, computer scientists have made great strides in the detection and diagnosis of breast cancer. This is particularly relevant in the realm of breast ultrasound and mammography, with AI-driven models outperforming human doctors in their detection of malignant tumors.
In one study conducted at Stanford, AI correctly identified malignant tumors from detections from mammograms, with a rate of 8.6% higher accuracy than even the most experienced radiologists. Perhaps most impressively, it was able to achieve the same rate of accuracy with marginally lower false-positive detection rates. This is extremely meaningful since false positives can cause undue and unnecessary stress for patients, leading to wasted resources and extra costs for medical care.
How AI Works in Breast Cancer Diagnosis
So how does AI actually work in diagnosing breast cancer? In many cases, AI functions in tandem with conventional medical approaches, such as breast imaging, to detect signs of malignancy. For example, a powerful AI-based system could be trained on a huge database of medical images in order to “learn” the characteristics of a healthy breast versus a malignant one. This system could then scan one image after another and identify tumors with greater accuracy than a human doctor.
Benefits of AI in Diagnosing Breast Cancer
The benefits that AI brings to breast cancer diagnosis are numerous. AI-based systems are considerably faster than human doctors, being able to detect tumors in a fraction of the time. AI-driven tools also boast a much higher accuracy rate than human doctors, meaning that far less common mistakes are made in diagnoses. From a healthcare infrastructure standpoint, this can reduce the amount of time wasted on missed diagnoses and unnecessary treatments, saving patients and doctors both time and money.
Finally, AI-based systems are significantly more cost-effective than their human counterparts. When first-line imaging is utilized, AI diagnostic tools can be used to reduce the cost of conventional medical care. By automating the screening, it’s possible to eliminate the need for costly follow-up treatments, thus reducing the overall cost of care.
The potential of AI-based systems to revolutionize medical care, particularly in the diagnosis of breast cancer, cannot be denied. Rather than continue to rely solely on human doctors and their limited resources, we’ll soon be able to tap into a powerful tool powered by the advancements of artificial intelligence.
Although the implementation of AI into medical care is just beginning, it will undoubtedly become an essential part of healthcare in the coming years. With its unmatched accuracy, speed, and cost-effectiveness, AI will soon come to be seen as the most reliable tool for diagnosing diseases like breast cancer. We are only now starting to see the potential of AI in healthcare, and we can’t wait to see what the future holds.