JSTOR Daily

Estimation and Inference of Heterogeneous Treatment Effects using Random Forests

Many scientific and engineering challenges—ranging from personalized medicine to customized marketing recommendations—require an understanding of treatment effect heterogeneity. In this article, we ...
ascopubs.org

Using machine learning to predict mortality in older patients with cancer: Decision tree and random forest analyses from the ELCAPA and ONCODAGE prospective cohorts.

Prediction of treatment (tx)-induced fatigue in breast cancer (BC) patients (pts) using machine learning on genome-wide association (GWAS) data in the prospective CANTO cohort. This is an ASCO Meeting ...
Hackaday

Training Bats In The Random Forest With The Confusion Matrix

When exploring the realm of Machine Learning, it’s always nice to have some real and interesting data to work with. That’s where the bats come in – they’re fascinating animals that emit very ...
JSTOR Daily

Machine-Learning Algorithms to Code Public Health Spending Accounts

Objectives:Government public health expenditure data sets require time- and labor-intensive manipulation to summarize results that public health policy makers can use. Our objective was to compare the ...
Popular Mechanics

This Is How Algorithms Will Evolve Themselves

Machine learning is hard. Algorithms in a particular use case often either don't work or don't work well enough, leading to some serious debugging. And finding the perfect algorithm–the set of rules a ...
Science Daily

Scientists use machine learning to predict diversity of tree species in forests

Researchers used machine learning to generate highly detailed maps of over 100 million individual trees from 24 sites across the U.S. These maps provide information about individual tree species and ...