Nature

Fast prediction of personalized abdominal organ doses from CT examinations by radiomics feature-based machine learning models

The X-rays emitted during CT scans can increase solid cancer risks by damaging DNA, with the risk tied to patient-specific organ doses. This study aims to establish a new method to predict patient ...
Frontiers

Coarse to superfine: can hyperspectral soil organic carbon models predict higher-resolution information?

Introduction: Modeling and mapping of soil organic carbon concentration and distribution at the pedon scale is a current knowledge gap that can be addressed by laboratory-based hyperspectral imaging ...
C&EN

Predicting Impact Outcomes and Maximum Spreading of Drop Impact on Heated Nanostructures Using Machine Learning

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Over the past decades, the advancements of software development ...
Nature

Predicting corrosion inhibition efficiencies of small organic molecules using data-driven techniques

Selecting effective corrosion inhibitors from the vast chemical space is not a trivial task, as it is essentially infinite. Fortunately, machine learning techniques have shown great potential in ...
C&EN

Support Vector Machine Classification and Regression Prioritize Different Structural Features for Binary Compound Activity and Potency Value Prediction

In computational chemistry and chemoinformatics, the support vector machine (SVM) algorithm is among the most widely used machine learning methods for the identification of new active compounds. In ...