What are the best machine learning applications? There are many but three of the best machine learning applications are in machine learning for medical diagnosis.
I was recently talking to a friend of mine who had been reading this blog (thanks pal!). He was asking me “why care about machine learning? What about it motivates you? Should we be concerned about machine learning?”.
What great questions I thought.
I think answering them could make for an interesting post. It would undoubtedly be more interesting than a post on my limited progress to date with the course (I got distracted by holidays. They were great).
Over the next few months, I will be doing a series of more detailed ‘focus posts’ on different topics within machine learning and artificial intelligence. However, today I’ll give you a starter for ten to whet your appetite.
I love machine learning for it’s potential to improve medical diagnosis and drug development. This is one of the best machine learning applications.
What is machine learning?
Before answering my friend’s questions in more detail, I thought I’d take a step back and explain what machine learning is.
To do this, I will quote noted machine learning expert Andrew Ng. I have taken this explanation from the introduction to his Coursera course on machine learning. He says:
“Machine learning is the science of getting computers to act without being explicitly programmed.
In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome.
Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level artificial intelligence.”
To summarize, machine learning is programming computers to learn to solve problems.
What are the best applications of machine learning?
Sounds pretty cool right? So why care about machine learning?
For me, the potential to gain understanding through machine learning is incredible.
Machine learning science uses probability and statistical analysis to answer questions.
I love being able to solve real problems with maths in a way that is accessible with some code and pressing run on a computer program. Getting the computer to do all the leg work for me while I sit back with a cup of tea is significantly more appealing than spending days in front of a blackboard or on a calculator.
With machine learning, we can take in infinity more data than previously possible to map out trends that will increase our understanding of the universe.
You can see this increase in understanding the applications of machine learning for medical diagnosis.
The application of machine learning for medical diagnosis
As I mentioned in a previous post, I love problem-solving. Machine learning gives me the opportunity to do this at scale.
One of the best ways of implementing this is for machine learning for medical diagnosis.
These problems can be for fun, like in my mission to define success or life-changing.
We are now seeing the application of machine learning for medical diagnosis. There is an increasing field of study in many medical research centers using machine learning to understand diseases better.
As a result, new innovative treatments are coming to light. I’ll share a couple of examples with you here:
- UCL in the UK is using ML to understand better how drug treatments will work for people who have suffered a stroke.
- Massachusetts General Hospital just published this paper on how they have used machine learning to predict the risk of developing C. difficile infection
- This paper documents how several groups have been making developments in our understanding and treatment of cancer
These are just a couple of examples I’ve seen recently but this is a link to another site that talks about 7 uses of ML in medicine: here čÖé
Should we be concerned about machine learning applications?
Whether or not we should be concerned about machine learning is an interesting question. I know there has been some bad press recently about artificial intelligence and the rise of the machines to take over the world.
I don’t believe that.
Even if it were possible, I’m not convinced. Anyone who like I have spent 10 minutes online attempting to pry information out of their banks latest attempt at a Customer Service chatbot before casually throwing their laptop out of the window, will agree that we’re a long way off the age of robots.
I hope I have convinced you-you need not be afraid, but just in case here’s another article on the topic:
Fear and loathing: A smart summary of ML and how it is used that talks about whether we should be concerned about machine learning
Back to the course…
Now I should get back to doing the programming course.
I hope that answers the questions on why care about machine learning and whether or not you should be concerned about machine learning.
Furthermore, I hope you feel enlightened on the application of machine learning for medical diagnosis.
I should probably get back to the course.
Let me know your reasons for being interested in machine learning in the comments or by subscribing to the email. You can find the link below the posts on mobile or in the right-hand bar on the desktop.
I look forward to hearing from you!
Are you also looking to learn to code? Here’s my post about how I found which course to begin learning to code. I hope it helps you.