I know cancer can be beaten
If you are old enough you will recognize the words of John Wayne. After he beat cancer the first time, he made many public service announcements to encourage others. It seems that the artificial intelligence (AI) researchers have taken those words to heart.
They are using AI to help fight cancer. They call it deep learning
What does AI deep learning do
Researchers are applying AI deep learning functions to help medical professionals catch mistakes in radiology. As we all know, human radiologists can make mistakes and misread a scan.
AI is being developed to read those scans and help reduce those errors. These robots are designed to reduce false positives in breast cancer detection. Plus, they are contributing to reducing the number of unnecessary surgeries that take place each year.
Then, AI deep learning helps with real-time analysis of polyps during colorectal screenings. It is hoped that AI deep learning will help defeat cancer.
How does AI deep learning do this
The deep learning AI works through algorithms, but these algorithms need three things to work correctly.
First, they need data brought into the system. Called input data this is simply information being sent to the algorithms.
Second, these algorithms need to produce results. This is called output data. Researchers examine the results and see how accurate the AI deep learning process was.
Third, researchers provide feedback. Researchers send their graded results back to the machine.
Because AI deep learning uses machine learning algorithms, the third step is necessary. The machine can’t learn if it does not know where it made its mistakes.
What powers AI deep learning
It is here where everything gets fairly technical. The answer will be very simplistic and skip a lot of the technical terminology. The real power behind AI deep learning is neurons.
These neurons are limited in a way. Single neurons make single decisions. They are not multi-functional brains that can grasp complex ideas. On the other hand, researchers have found that by combining neurons into a network more decisions can be made.
It all depends on how many input neurons are placed together and how many output neurons are used. The more neurons used, the more refined the scale and decision making. Also, the more layers of neurons the more complex the analytical ability of AI deep learning becomes.
The more sophisticated the neuron network, the better chance at detecting cancer and reducing false positives.
Some Final Thoughts
There are three hopes that come with AI deep learning. First, it is hoped that this machine learning technology will help people beat cancer like Mr. Wayne once did. Second, it is hoped that this technology will help those in rural areas where doctors are not found.
The third hope is that the AI deep learning process will present better, clearer data so that diagnosis will be more accurate. The medical world most likely would love to see these hopes become a reality.