An estimated 1.9 million people receive a cancer diagnosis each year in the United States. Often, cancer is a life-threatening condition, though a patient’s odds are often better if the cancer is detected early. The issue is that approximately 50 percent of cancers aren’t found until they’re in an advanced stage, and that can often lead to worse outcomes. Fortunately, technology is working to make early cancer detection easier. Here’s a look at how artificial intelligence (AI) is assisting with early cancer diagnosis.
The Challenge of Identifying Cancer in Patients
Many cancer detection strategies rely heavily on radiological images. Those images allow radiologists to examine various parts of the body, looking for changes or anomalies that could indicate cancer. Then, further testing – such as biopsies – can occur to confirm the diagnosis, allowing medical providers to create a treatment plan.
However, spotting early signs of cancer in radiological images isn’t always simple, even for highly trained and very experienced radiologists. Some of the initial changes are incredibly subtle, which can cause very treatable cancers to get overlooked. As a result, the cancer has time to grow and spread before it’s ultimately noticed on radiological imaging. By that point, a patient’s odds of a positive outcome often decrease, potentially dramatically.
Ultimately, this challenge was somewhat unavoidable for quite some time, even among some of the nation’s best radiologists. However, AI is working to create better odds for patients, all by making early detection easier to achieve.
How AI Is Assisting with Early Cancer Diagnosis
AI technology is assisting radiologists with early cancer diagnosis by analyzing images to identify anomalies that could indicate the presence of cancer. Often, these AI-backed tools can find issues in the images that aren’t easily seen by a person. This can include tiny cancers that aren’t easily observed or signs of changes that could indicate the development of cancer later.
Generally, AI detection tools work similarly. The technologies are given access to large amounts of data, typically radiological images or similar visual diagnostic imaging. The goal is to teach the AI what cancers or precancerous changes look like, even if the evidence is minute within the broader image. Then, AI solutions can scan patient images to look for similar anomalies, flagging any issues it finds for further examination by a medical professional.
With this process, AI may identify radiological anomalies that even trained professionals may overlook. As a result, this could lead to early diagnosis for patients who are in the beginning stages of cancer development. In turn, creating an effective treatment plan is often more likely. Plus, treating the cancer early can mean a less challenging experience for the patient overall, which could also lead to better outcomes.
The Road Ahead Is Still Long
While AI technology is already assisting with cancer identification in patients, the road ahead is still long. Solution designers are often stymied by limited available datasets, which makes it harder to train an AI effectively.
Additionally, some of the early development of these AI technologies require significant input from radiologists. Along with being a time-consuming task, this creates new challenges. For example, an AI may accidentally be trained to overlook an anomaly because a radiologist didn’t annotate it since it was subtle enough to get missed.
Still, as time passes, the technology will grow and evolve. Ultimately, AI would likely never become a replacement for a radiological imaging analysis by a trained professional. Instead, it’s a supportive technology, one that could reduce the odds of an issue being missed during a radiological review.
The research into using AI in this capacity is ongoing, and progress is made on a regular basis. As a result, AI cancer detection tools will likely continue to grow and develop, as well as become a more standard part of the patient assessment process. But the human touch will remain part of the equation, allowing professionals and technologies to effectively work together to make early cancer diagnosis more accessible.
How Translators and Interpreters Improve the Patient (and Provider) Experience
Ultimately, AI is altering the cancer detection equation, potentially making early diagnoses easier to make and quick treatment increasingly possible. While that in and of itself improves the patient experience, it’s critical not to overlook the importance of effective communication. By partnering with a leading language services provider, medical facilities can enhance patient communication, improving the experience for both patients and providers.
If you’re looking for top-quality translators, Acutrans offers accurate certified document translations in 24 hours and has specialized translation services designed explicitly for the medical sector. Additionally, if you require experienced interpreters, Acutrans also meet that need. Our skilled team offers video remote, over-the-phone, and on-site interpretation services that cover more than 200 languages, and we can provide industry-specific interpretation services for the healthcare sector. Contact us for a free quote today.