Exciting things are happening in the world of Artificial Intelligence (AI). With AI's influence reaching farther and farther into our everyday lives, it’s no wonder companies are investing millions of dollars into its development. The crazy thing is that most of us are virtually clueless about how much we interact with AI every day.
One big component of AI is machine learning. Machine learning in exactly what it sounds like - machines "learning". It's technology getting smarter as it takes in more and more data. And this has some interesting implications for the progress and development of fertility apps.
What is Machine Learning?
Machine learning refers to developing technology in such a way that it can learn and improve without being programmed for a new function.
Specifically, it learns by data input. The more data entered, and specifically the more accurate data entered, the more the machine can evaluate and adjust based on that data. But it’s even more than that. Ideal machine learning can recognize fuzzy rules or patterns and adjust accordingly.
Examples of Machine Learning...
Did you know your email spam catcher does more than just rule out emails with a rude word in the subject. It uses machine learning. As the spam catcher receives more and more spam, they can more accurately catch it and remove it for you. Even if new sources send you spam, they can identify it as spam based on the patterns of spam from previous sources.
This is one way you are probably interacting with machine learning every day, but it affects a lot of aspects of your life. Financial institutions use it to establish your credit scoring. Health institutions are using it to develop better tumor detection. In short, machine learning is having a massive impact on all levels of society.
How Does it Work?
The actual workings of machine learning can be boiled down to math. Machine learning uses algorithms to find patterns in data and process it accordingly. For most of us, that sounds like magic, but for mathematicians it’s very scientific and calculated.
Regression techniques are a form of algorithms that help with data processing and prediction. In fact, Dot uses a form of regression analysis (called Bayesian Linear Regression) to give you the best possible information about your cycle. If that sounds like we’re speaking Swahili to you, we’re not. It basically means we use algorithms to interpret data to predict what is most likely to happen in the future.
Armed with these tools, Dot can make super helpful predictions about your cycle and your fertility chances. Then you can make informed decision about family planning and birth control. Pretty amazing what AI can do!
What’s The Impact On Your Fertility?
When it comes to fertility apps, machine learning gets us one more step toward more accurate results. It helps us estimate your fertility risks each day, and identify your high risk days more accurately. The more period dates you enter, the more Dot can hone in on your fertile window. And it can help you be more prepared to avoid unexpected visits from your period. With Dot, machine learning also functions to alert you to any unknown health concerns based on the length of your cycle. So the more we develop machine learning, the less you have to process and sort through fertility data yourself.
Want to learn more about the innovations going on at Dot? Check out our research initiatives!
Chang, Betty. "Investment in Artificial Intelligence Is Essential for Our Future Health." The Independent. April 29, 2018. Accessed July 17, 2018. https://www.independent.co.uk/voices/artificial-intelligence-machine-learning-computers-global-healthcare-malaria-facebook-a8327901.html.
"Dot Fertility App Efficacy Study." Dot Period & Fertility Tracker. Accessed July 17, 2018. https://www.dottheapp.com/dot-research.
"How Machine Learning Works." The Economist, May 14, 2015. Accessed July 17, 2018. https://www.economist.com/the-economist-explains/2015/05/13/how-machine-learning-works.
P, Daryna. "How Can Machine Learning Revamp Your Mobile App?" Ruby Garage(blog). Accessed July 17, 2018. https://rubygarage.org/blog/machine-learning-for-mobile-apps.
"What Is Machine Learning? | How It Works, Techniques & Applications." Math Works. Accessed July 17, 2018. https://www.mathworks.com/discovery/machine-learning.html.