Mr.Chongwei Shi Enhances Genomic Analysis Through Signal Processing and Machine Learning Integration for Gene Identification

A signal-processing–based framework converts DNA sequences into numerical signals to identify protein-coding regions. By integrating spectral ...
IEEE

Quo Vadis, Quantum Machine Learning?: Quantum kernel methods meet Earth observation

Abstract: The analysis of satellite images has attracted significant research interest due to its numerous applications and unparalleled scalability in Earth observation (EO). Although artificial ...
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, ...
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

Comparison of machine learning methods for predicting ground-level ozone pollution in Beijing

With the accelerating pace of urbanization, air pollution has emerged as a critical global challenge, where ozone (O 3) concentration dynamics have become a pivotal indicator of atmospheric quality ...
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 ...
IEEE

A Method of Kernel Principal Component Analysis and Machine Learning Algorithms for Fault Diagnosis of Power Transformers

Abstract: As one of the most important equipment in the power system, it is of great significance to conduct fault diagnosis research on transformers. Aiming at the problem of difficult selection of ...