Nature

Evaluating the factors influencing accuracy, interpretability, and reproducibility in the use of machine learning classifiers in biology to enable standardization

The complexity and variability of biological data has promoted the increased use of machine learning methods to understand processes and predict outcomes. These same features complicate reliable, ...
Nature

A stacking ensemble machine learning model for predicting postoperative axial pain intensity in patients with degenerative cervical myelopathy

Machine learning (ML) has been extensively utilized to predict complications associated with various diseases. This study aimed to develop ML-based classifiers employing a stacking ensemble strategy ...
EurekAlert!

Strategic reuse of rapid antigen tests for coagulation status assessment: an integrated machine learning approach

• Repurposed COVID-19 RATs provide an ideal platform for observing differences in blood coagulability. • Random Forest image classification algorithms can facilitate rapid coagulation status ...
Healio

Machine learning model predicts small airways disease in patients with asthma

Please provide your email address to receive an email when new articles are posted on . A machine learning classifier was trained on capnogram features. The model’s probability output inversely ...
Labroots

Novel Multiplex Diagnostic Assays for Serology

Lyme disease is a high-incidence infectious disease with a global prevalence of 14.5% of the world's population. Two-tier serology is currently the primary diagnostic test for Lyme disease; however, ...
Visual Studio Magazine

Predicting the Future Using Azure Machine Learning

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...