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 ...
insideHPC

TECH TIP: An Introduction to Random Forests

Random Forests Co-Developer Dr. Adele Cutler visited Salford Systems in San Diego, CA. While she was visiting, she gave the staff a few quick presentations and interviews related to the popular Random ...
ascopubs.org

Classifying Stage IV Lung Cancer From Health Care Claims: A Comparison of Multiple Analytic Approaches

Our study used the linked SEER-Medicare data. The patient samples included fee-for-service Medicare beneficiaries diagnosed with lung cancer from 2010 to 2011 (development cohort) and 2012 to 2013 ...
EurekAlert!

Chip design with machine learning: a survey from algorithm perspective

This paper comprehensively surveys existing works of chip design with ML algorithms from an algorithm perspective. To accomplish this goal, the authors propose a novel and systematical taxonomy for ...
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 ...