Nature

Optimizing unsupervised clustering of electrochemical impedance spectra via normalization and dimensionality reduction

Electrochemical impedance spectroscopy (EIS) is entering an exciting stage of development as machine learning–driven (ML) spectral analysis begins to complement traditional equivalent-circuit fitting ...
Scientific Research Publishing

Performance of Different Machine Learning Algorithms for Credit Risk Classification ()

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...
Nature

A concept-based interpretable model for the diagnosis of choroid neoplasias using multimodal data

Diagnosing rare diseases remains a critical challenge in clinical practice, often requiring specialist expertise. Despite the promising potential of machine learning, the scarcity of data on rare ...
eLife

Inferring the time-varying coupling of dynamical systems with temporal convolutional autoencoders

This important work presents a novel approach to infer causal relations in non-stationary time series data. To do so, the authors introduce a novel machine-learning model of Temporal Autoencoders for ...
Frontiers

SABO-ILSTSVR: a genomic prediction method based on improved least squares twin support vector regression

In modern breeding practices, genomic prediction (GP) uses high-density single nucleotide polymorphisms (SNPs) markers to predict genomic estimated breeding values (GEBVs) for crucial phenotypes, ...