BIOENGINEER

Machine learning predicts self-reported anger improvement in teens

A machine-learning analysis found that survey data describing meditation habits, daily behavior and lifestyle can predict ...
BIOENGINEER

Interpretable machine learning for identifying cost drivers of inpatient traditional Chinese medicine services in a tertiary hospital in China

A retrospective machine-learning study of 1,532 hospitalizations found that treatment-item charges, length of stay and herbal medicine costs accounted for about 81% of modeled inpatient traditional ...
Healio

AI ‘may offer an efficient way’ to detect colorectal neoplasia, but more research needed

Two machine learning models demonstrated high accuracy in identifying adenomas and sessile serrated lesions, although more ...

"I want you to explain the 'why' behind GWR and Random Forest results"—Creating maps that interpret spatial statistics and machine learning model results for field operations

Introduction"I finally built a model with good accuracy using GWR or Forest-based Regression, but when I showed it to my boss, they asked, 'I understand this district is high, but why is it high?' and ...
Visual Studio Magazine

Random Forest Regression Using C#

Random forest regression is a tree-based machine learning technique to predict a single numeric value. A random forest is a collection (ensemble) of simple regression decision trees that are trained ...

“I only have point data for machine learning explanatory variables” — Rasterizing distance, density, and proximity for use as predictive model inputs

Introduction“I want to predict demand using GWR or Random Forest, but all I have is point data like facility locations or ...
Visual Studio Magazine

Random Forest Regression and Bagging Regression Using C#

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the random forest regression technique (and a variant called bagging regression), where the goal is to ...