Artificial intelligence or AI or Artificial Intelligence or Mechanical Intelligence: Cancer is a very difficult disease for treatment. With over a hundred known species, each responding differently to body and body treatment (and dozens of other factors), oncologists definitely have a lot of work.
As can be seen the technology and specifically the engineering learning (Artificial intelligence) could soon make their job a little easier.
The IBM Watson supercomputer has a mechanical learning application for personalized cancer treatment for some time.
It examines over 600.000 medical reports and 1.500.000 anonymous patient envelopes and clinical trials, and the data it analyzes are designed to help scientists involved in the treatment. Currently, doctors rely on books, medical journals and clinical research to treat incidents. 
But research from a post-medical school could advance them Results tests on artificial intelligence applications (Artificial intelligence) to design a better and more effective treatment.
And IBM is not alone.
Her DeepMind Google learns how to best apply radiation therapy to cancer patients. It examines how exposing patients to dangerous doses of radiation can stop tumors by limiting the damage they can cause to healthy parts of the body. Doctors today use 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 partitioning, requires a doctor to know precisely the infected areas, which can not be dealt with only by a three-dimensional scan of the patient's volume. Adding complexity, head, neck, brain or spine, doctors have to make tough decisions on how to apply optimal radiation therapy without destroying critical areas.
Google DeepMind Artificial intelligence
DeepMind works with researchers at University College Hospital in London to develop artificial intelligence systems that could automate major parts of this process.
According to team DeepMind:
Clinicians will remain responsible for λήψη decisions on radiotherapy treatment plans, but it is hoped that the segmentation procedure could be reduced from four hours to around one hour.
To convert this process, DeepMind will analyze 700 anonymous scans from former patients suffering or suffering from head and neck cancers. The hope is to develop an algorithm that can identify the best targeting areas from scans automatically.
Over time, the team hopes that this approach can be applied to the treatment of cancers and other parts of the body.
