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Ethan Taft August 18, 2017

A few weeks ago, our blog featured a post about k-means clustering, an unsupervised machine learning method. We use unsupervised methods when we don’t have an explicit idea of what patterns exist in a dataset. Clustering can help us surface insights about groups that exist in the data that we may not know about. To separate data into clusters, k-means first needs to calculate the distance between each data point. That distance is used to help define the “similarity” between two points and is normally calculated using some continuous technique…

Yannick Van Huele August 01, 2017

The two main algorithms used for binary classification in healthcareai are logistic regression with a Lasso penalty (from now on, simply the Lasso) and random forests.  In this post, we’ll visually explore the behavior of the Lasso and random forest models by working with some artificial 2-dimensional datasets to help build intuition about how the algorithms work and on what type of datasets each algorithm can perform well on. All the Lasso and random forest models plotted below were built using the healthcareai R package (the plots were built in…

Hanlei Zhu July 21, 2017

Clustering is an unsupervised machine learning technique, with several valuable applications in healthcare. Consider the situation where a model is trying to predict a patient’s likelihood of having diabetes. In most cases, a set of outputs (label of whether a person has diabetes or not) is associated with inputs (attributes like age, weight, blood pressure and so on). One can train a supervised classification model, like random forest to learn the patterns associated with the output. Then, if a new patient comes in, the trained classifier can predict if the…

Shufang Ci July 14, 2017

Neural networks are currently a hot field, especially in healthcare. People have talked about using them to score pathology slides and mammograms, and mine the EMR for connections. However, they are very confusing. According to Maureen Caudill, a neural network is “a computing system made up of a number of simple, highly interconnected processing elements, which process information by their dynamic state response to external inputs.” Can’t figure out what is going on in Maureen’s definition? No worries. At healthcare.ai, we are all about making machine learning transparent. Let’s step…

Ethan Taft June 30, 2017

Most of us have used an online shopping retailer like Amazon, and we’ve all most likely used an online movie service like Netflix. Have you noticed the recommended items to purchase or the recommended movies to watch? Amazon and Netflix build recommendations using similarity scores. One of the popular methods of building and offering a recommendation is called collaborative filtering. What is collaborative filtering and how does it work? Here is the logic behind collaborative filtering: If Joe and Jill each buy the book, “Machine Learning with R,” they now…

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