7 Ways AI is Helping Doctors Diagnose and Treat Cancer
7 Ways AI is Helping Doctors Diagnose and Treat Cancer
What is the first thing that comes to your mind when you hear about cancer? Did you say “Death?” If you did, you are right. According to the World Health Organization report, 20% of males and 17% of females develop cancer during their lifetime, and 12.5% of males and 9% of females die from the disease. Cancer is the second leading cause of death after a heart attack, killing more than 500,000 people every year.
Thankfully, technology is here to change all that for good. We have already seen artificial intelligence outsmarting diseases like flu, but can it take on the likes of cancer. Many experts believe that it can. In this article, you will learn how artificial intelligence and supercomputers can join forces to defeat cancer. Read on to find out more.
1. Drug Design
Before the advent of supercomputers, creating a new drug to cure a dangerous disease requires a considerable investment and a lot of time. So much lapsed time occurred that the real benefits of modern technology on a disease — never reach the patients. With supercomputers, researchers can now identify new drugs and treatment faster and with less investment.
For example, Shuxing Zhang of MD Anderson Cancer Center has already used supercomputers to scan 1500 drugs to determine which drugs can inhibit TNIK. TNIK is an enzyme responsible for cell signaling in patients with colon cancer. The new technology allows quick discovery of the right drug to cure dangerous diseases.
2. Immunotherapy
Immunotherapy is a treatment that boosts the body’s natural defense mechanism so it can fight with cancer. The problem with immunotherapy is that it does not work on all cancer patients. It might work on some but does not work on others. Supercomputers can help researchers identify tumor responses of immunotherapy and see how different patient bodies react to this treatment. Understanding the variables provides actionable clinical knowledge from big and diverse data sets.
Clinical information gained from data sets means that researchers can use this information to develop active clinical trials and can critically analyze genetic data related to immune proteins. As a result, we might see more effective cancer treatment, and more patients will be able to defeat cancer.
3. Surgery
One of the most popular treatment methods for cancer is surgery, but sometimes surgery is not the safest. There could be many complications that can occur during and after surgery. For instance, if a doctor removes too little tumor, there is always a risk of relapse, which can harm the patient.
Researchers at the University of Texas have used supercomputers to perform laser treatment on a canine tumor without any surgeon. With the number of images and data we have today, researchers and surgeons can rely on surgical simulations. Now, scientists are trying to replicate the same thing with portable systems. The day when artificial doctors and surgeons will operate patients is near. You never know you might see a robot perform surgery within a few years.
4. Radiation and Proton Therapy
Another standard mode of cancer treatment is X-Ray radiation, but it is slowly being replaced by a new treatment method known as proton therapy. In proton therapy, a beam of the proton is fired at the cancer cells to destroy them. The advantage of this treatment is that it does not damage the surrounding tissues. The sheer precision of this treatment forces the devices to be perfectly calibrated, and the margin for error is almost non-existent. Researchers are also using supercomputers to study new types of X-rays that combine real-time imaging and treatment to replicate proton therapy.
5. Cancer Diagnostics
We all know that diagnosing cancer is the first step. The faster you diagnose the disease, the easier it is to cure. With the advancement in medical sciences, new types of DNA tests and sensitive body scans are being developed, which will help in quickly diagnosing the disease. Then there are nanosensors implanted in your bloodstream, which will notify about cancer cells.
The problem with all these new tests is that it can be dangerous to test them on patients, so scientists are using supercomputers to create simulations that help them test the effectiveness of these new tests.
Scientists have developed a new diagnostic device that they are calling as a nanopore. This device goes through a thin hole in the membrane and is capable of DNA sequencing inside the body. Moreover, it detects signs of cancers as DNA molecules pass through. Researchers are also working on developing nanocarriers, which can be used to capture the DNA molecule.
6. Genomics
A single human genome contains 3 billion base pairs. Three billion is a massive number to identify where a mutation can occur — it’s virtually impossible, manually. That is where artificial intelligence and machine learning comes in. Both these technologies are great at identifying patterns from massive data sets. When you combine that with the power of a supercomputer, you will be able to analyze these billions of pairs in minutes, not weeks. Speedy-pairing-analysis allows medical scientists to develop more target therapies that can eliminate the roots of cancer in the patient’s body. That is not all; supercomputers have also helped scientists identify cancer risk factors and see how every cancer patient reacts to different treatments.
7. Patient-Specific Treatment
Just like in app development, one size does not fit all when it comes to cancer treatment. Every patient is different and will react differently to different treatments. Researchers are currently divided concerning correct protocols for the approaches of cancer treatment. Some might use data mining techniques while others prefer a mathematical model. Thomas Yankeelov, head of Center of Computational Oncology, is in the latter camp.
Thomas Yankeelov said,
“If you have a model that can recapitulate how tumors grow and respond to therapy, then it becomes a classic engineering optimization problem. ‘I have this much drug and this much time. What’s the best way to give it to minimize the number of tumor cells for the longest amount of time?”
Researchers are looking for ways to predict how effective a particular treatment will be for a specific patient. Ai Trends can help with that by identifying patterns and make predictions.
How do you think artificial intelligence and supercomputers will impact cancer treatment in future? Feel free to share it with us in the comments section below.
Image Credit: Peter-Rejceck-shutterstock
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