Frank Mendoza of Catalytics gave a presentation on analyzing the same Wisconsin Cancer Data Set that we presented with the HealthCare.AI toolkit in November 2017. It was interesting to see how Azure Machine Learning works at a higher level with intuitive, graphical predictive analysis as compared to Healthcare.AI. I intend to add Azure Machine Learning …
On November 28, 2017, Dan Wellisch led a second revision of his October 2017 discussion. In this discussion, the Breast Cancer Wisconsin (Diagnostic) Data Set was used. Dan also revised his slides to show the overall Machine Learning process along with graphs that can help one determine which Machine Learning model performs best on the …
If you were to perform a daily web search for “Machine Learning and Cancer”, you may find more companies each day that are using Supervised Machine Learning to perform Predictive Analytics on cancer data sets. There is Tempus, here in Chicago, IL, Berghealth in Framingham, MA, and FlatIron Health in New York, NY, as examples. …
On October 30, 2017, Dan Wellisch, presented the Python version of the HealthCare.AI open source library. He went through a basic example of a diabetes data set where the goal was to predict 30 day re-admissions for diabetes patients. He discussed the process of training several models, selecting the highest performance one, saving that model, …
On September 26, 2017, Dan Wellisch, Organizer of the Chicago Technology For Value-Based Healthcare Meetup, presented a detailed breakdown of the Linear Regression Model. The Linear Regression Model is the first model that gets taught to Data Science students. In its simplest form, there are 2 variables, an input (or feature) variable and an output …
