If illnesses and sickness represents what’s cruel and bad about our world, cancer must certainly be the mere representation of this. Cancer is not only cruel and bad, it’s also unfair and by all means harmful and mischievous. Because the thing is, you see, that cancer does not discriminate and neither is it in any way predictable. Cancer can be lurking around the corner without anyone knowing and it can make whoever sick, whenever. Regardless of how young and strong you are, regardless of how healthy of a life you are living. It will never guarantee you any absolute safety from being sick of cancer. One cannot simply escape cancer, so one searches for the best solutions and options available for treating such a horrendous disease.
The art of automatisation
When talking about modern day solutions for treating such unpredictable, complex, complicated and multifaceted diseases such as cancer of its various forms one must certainly include modern day technology in the conversation. Technology plays a major role in treating and even curing cancer nowadays, and the technology is forever evolving. Combining the knowledge of technology that we today have with all the medical knowledge of modern day has helped evolve cancer treatment beyond limits of what we could’ve hoped for 20-30 years ago. Machines does of course play their role and machine learning treatment planning is as relevant as it has ever been. When letting advanced machines take care of the so important planning part of the treatment the manpower can instead be focused on the more pure medical parts.
This is because of something called automated planning, where the machines learn and can play a vital role in a successful and by far effective treatment of patients sick with various forms of cancer. This chapter is called The art of automatisation, and it is by all means an art, and a very important one in our society today. There are so many components of our society that are today automated, rather than manual, that we nearly no longer think about it. The technology behind machine learning, automated planning and treatment planning is fascinating and deep learning segmentation is an important part, whereas a model of deep learning can ideally segment organs in less than 45-60 seconds.