Joint research led by Sosuke Ito of the University of Tokyo has shown that nonequilibrium thermodynamics, a branch of physics ...

A machine learning model bests traditional methods for predicting cirrhosis mortality among hospitalized patients.

If you rotate an image of a molecular structure, a human can tell the rotated image is still the same molecule, but a machine ...

Researchers integrated machine learning with multi-tiered validation to identify FDA-approved non-lipid-lowering drugs with lipid-modifying potential. From 3,430 drugs screened, 29 candidates emerged.

Researchers present a machine learning framework that forecasts individual mental health deterioration using limited, real-world data from wearables and smartphones. This enables personalized early ...

Importantly, the use of a diverse set of machine learning algorithms—including linear models, ensemble methods, and non-linear classifiers—demonstrates the versatility and reliability of the selected ...

Background This study aims to develop an interpretable machine learning model using SHapley Additive exPlanations (SHAP) to predict favorable outcomes based on clinical, imaging, and angiographic data ...

Several machine learning (ML) algorithms have been applied to predict path loss values, and various features have been proposed as input features in ML models. This study proposed two new types of ...

Machine learning algorithms are computational models that allow computers to acquire knowledge and improve performance on a task by automatically learning patterns and rules from input data provided ...

The methodology involved gathering PRS-11 questionnaire data, performing street map crawling and prediction, conducting large-scale analysis of 114 student image evaluations using a CNN-BiLSTM-based ...