BMJ

Development of an interpretable machine learning model for frailty risk prediction in older adult care institutions: a mixed-methods, cross-sectional study in China

Objective To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced ...
Frontiers

Mapping stability and instability hotspots in Jiangsu’s vegetation: an explainable machine learning approach to climatic and anthropogenic drivers

Understanding vegetation stability is essential for evaluating ecosystem resilience and informing adaptive land management under changing climatic conditions. This study investigated the ...
C&EN

A New Pulsed Neutron-Gamma Density Logging Method Based on Gamma-Ray Spectra and Machine Learning

However, NGD faces several challenges associated with gamma-ray generation and attenuation complexities. Unlike GGD, which utilizes 0.662 MeV monoenergetic γ rays from a 137 Cs source, NGD employs ...
PNAS

Machine learning in chemistry

The Perspective by Tiwary et al. (8) offers a comprehensive overview of generative AI methods in computational chemistry. Approaches that generate new outputs (e.g., inferring phase transitions) by ...
Frontiers

Development and validation of a machine learning model based on multiple kernel for predicting the recurrence risk of Budd-Chiari syndrome

Background: Budd-Chiari syndrome (BCS) is a rare global condition with high recurrence rates. Existing prognostic scoring models demonstrate limited predictive efficacy for BCS recurrence. This study ...
TechRepublic

20+ Machine Learning Methods in Groundbreaking Periodic Table From MIT, Google, Microsoft

20+ Machine Learning Methods in Groundbreaking Periodic Table From MIT, Google, Microsoft Your email has been sent A new “periodic table for machine learning” is reshaping how researchers explore AI, ...
Microsoft

A periodic table for machine learning

Researchers from MIT, Microsoft, and Google have introduced a “periodic table of machine learning” that stands to unify many different machine learning techniques using a single framework. Their ...
IEEE

Benchmarking Quantum Machine Learning Kernel Training for Classification Tasks

Abstract: Quantum-enhanced machine learning is a rapidly evolving field that aims to leverage the unique properties of quantum mechanics to enhance classical machine learning. However, the practical ...
Scientific Research Publishing

Application of Machine Learning Methods in Parameter Prediction of Deep Lacustrine Oil Shale Reservoirs—Taking the Triassic Chang 7 in the Longdong Area as an Example ()

1 School of Earth Science and Engineering, Xi’an Shiyou University, Xi’an, China. 2 Key Laboratory of Petroleum Geology and Reservoir, Xi’an Shiyou University, Xi’an, China. In the course of oil and ...