Journal of Medical Internet Research

Using Machine Learning Methods to Predict Early Treatment Outcomes for Multidrug-Resistant or Rifampicin-Resistant Tuberculosis to Enhance Patient Cure Rates: Development and ...

Objective: This study compared a conventional logistic regression model with machine learning (ML) models using demographic and clinical data to predict outcomes at 2 and 6 months of treatment for MDR ...
The Lancet

Causal deep learning for real-time detection of cardiac surgery-associated acute kidney injury: derivation and validation in seven time-series cohorts

aMedical Big Data Research Center, Chinese The People’s Liberation Army General Hospital, Beijing, China bNational Engineering Research Center of Medical Big Data Application Technology, The People’s ...
IEEE

Improving Graph Embeddings in Machine Learning Using Knowledge Completion with Validation in a Case Study on COVID-19 Spread

Abstract: The rise of graph-structured data has driven major advances in Graph Machine Learning (GML), where graph embeddings (GEs) map features from Knowledge Graphs (KGs) into vector spaces, ...
IEEE

Evaluating Spatial Representativeness Across Multiple Scales for a Comprehensive Ground Validation Network Using Landsat Land Surface Temperature Data and Random Forest

Abstract: Land surface temperature (LST) products require rigorous validation before widespread application, and the spatial representativeness of ground validation sites plays a critical role in ...
WTOP News

Data Doctors: Is Google using my email messages to train AI?

A viral story from last year has been making the rounds again, claiming that Gmail automatically opted all users into a program that lets Google train its AI on your private emails and attachments. If ...