Cancer care has developed greatly over recent years with the induction of artificial intelligence. More patients are being treated early as AI technology is becoming more widely available for facilities across the globe. If you’re not familiar with how AI is being incorporated into cancer treatment, it’s time to start.
What is Artificial Intelligence?
At its most basic level, artificial intelligence (AI) is an algorithm or computer program that uses data to make informed decisions and predictions. Those who develop AI technology start by inputting a specific set of rules, known as instructions, that the computer will utilize to analyze data that it’s presented with.
Taking it even a step further, artificial intelligence can undergo machine learning. This is where the initial program teaches itself how to analyze and interpret data sets. This is particularly helpful for picking up patterns that aren’t keenly noticed by the human eye. As these AI algorithms are constantly undergoing machine learning, their ability to learn and interpret new data increases.
How is AI Being Used in Cancer Imaging?
One area where AI is being used regularly is cancer imaging. Traditionally, medical imaging is evaluated by a radiologist or another imaging professional. This takes time to evaluate the image and answer a variety of questions.
Most images that are evaluated are to answer a variety of questions, including:
- Is it cancer or a benign tumor?
- How fast is cancer growing?
- How far is the cancer spreading?
- Is cancer growing back after treatment?
AI cancer detection works to turn back an answer to these questions in seconds. Instead of an imaging technician evaluating the image to find their own determinations, the AI cancer imaging technology will evaluate the image first. Then, a radiologist or medical professional will view the image to verify the diagnosis.
AI cancer imaging is thought to help take a highly subjective process of assessing medical imaging and turn it into a more straightforward process. With machine learning for cancer imaging, researchers are hoping that this imaging will provide a more reliable approach to imaging diagnosis.
Can AI Help With Early Cancer Detection?
When it comes to treating cancer, doctors know that typically the earlier they can catch it, the more treatable it will be. This is why there are a variety of screening processes, including mammograms and pap tests, just to name a few. While these are effective forms of early cancer diagnosis, cancer care can be enhanced with AI cancer detection.
AI cancer screening is currently in use to help doctors assess the results of various imaging tests. However, new scientists use AI to decode the best algorithms for when patients should be tested. These algorithms take into account a person’s past imaging results to determine their likeliness of developing cancer in the future.
With machine learning, AI can essentially view all the mammograms that were taken five years ago of patients who ended up being diagnosed with cancer. Any similarities that AI can pick up on will help it to provide worthy predictions for new patients who have similarities in their mammogram imagery. The idea is to get them back in for more regular testing so if cancer develops, it can be caught as early as possible.
Another way that AI has been proven to help with cancer prognosis is by providing more reliable pre-screening results. When put head-to-head with doctors in a low-resource setting, AI was able to diagnose more patients with cervical precancers. This early identification is the key to giving better cancer care and diagnosis to patients.
How Does Genomics Factor into Treatment Options?
Cancer develops when specific genomics in the body are altered. When these damaged cells are allowed to multiply, they create cancer. Advanced genomic testing is helping to identify known DNA alterations in patients. This will provide an early diagnosis so that treatment can be provided as soon as possible.
Additionally, identifying these alternations will help an oncologist decide on the appropriate treatment. As the medical community learns more about cancer, customized treatment options are being designed to target individual DNA mutations.
When Will AI Tools for Cancer Imaging Be Ready for Real-World Applications?
Right now, sophisticated modeling software is helping international researchers around the globe enhance their cancer diagnosis and treatment. However, this technology isn’t widely available to all practicing oncology treatment facilities.
AI is still a fairly newer development. It’s regularly undergoing new testing to see how well it performs. Before a solution like machine learning for cancer can be trusted on a full scale, it needs to constantly be proven successful.
As with any type of technology, scientists who use AI to decode cancer prognosis are going to become more reliant on it. This is great when AI is working properly. However, this can prove tragic when it isn’t. With more testing and confirmation, the future of AI for cancer detection and image reading looks very positive.