Artificial intelligence or AI or Artificial Intelligence or Machine Intelligence: Cancer is a very difficult disease to treat. With more than a hundred known types, each of which responds differently to treatment depending on the carrier and the part of the body it is in (and dozens of other factors), oncologists certainly have a lot of work to do.
It seems that technology, and specifically machine learning (Artificial intelligence), could soon make their job a little easier.
IBM's Watson supercomputer has had a machine learning application for personalized cancer treatment for some time.
It examines over 600,000 medical reports and 1,500,000 anonymized patient and clinical trial files, and the data it analyzes is intended to help scientists who are involved in treatment. Currently, doctors rely on books, medical journals, and clinical research to treat cases. 
However, research from a post-medical school could advance the results of tests on artificial intelligence applications to design better and more effective treatment.
And IBM is not alone.
Google's DeepMind is learning how to best deliver radiation therapy to cancer patients. It's examining how exposing patients to dangerous doses of radiation can stop tumors while limiting the damage it can cause to healthy parts of the body. Doctors are now using a combination of past experience and current research to try to determine the best way to expose a body to radiation as part of a treatment.
This process, known as segmentation, requires a doctor to know precisely where the cancer is, which cannot be done with just a 3D scan of the patient's tumor. Adding to the complexity, whether it's the head, neck, brain or spine, doctors have to make difficult decisions about how to best deliver radiation therapy without damaging critical areas.
Google DeepMind Artificial intelligence
DeepMind is working with researchers at University College Hospital in London to develop artificial intelligence systems that could automate large parts of this process.
According to the DeepMind team:
Clinicians will remain responsible for making decisions on radiotherapy treatment plans, but there is hope that the segmentation process could be reduced from four hours to around one hour.
To transform this process, DeepMind will analyze 700 anonymized scans from former patients who have or have had head and neck cancers. The hope is to develop an algorithm that can identify the best target areas from the scans automatically.
In time, the team hopes that this approach can be applied to treating cancers in other parts of the body.
