Tag: Feature Selection

A hybrid deep learning and radiomics framework can detect subjective cognitive decline, the earliest preclinical stage of Alzheimer's disease, from ...

A new machine learning study identifies ten key bacterial species and visualizes the abundance thresholds that separate healthy vaginal microbiomes ...

A new graph-attention-based generative adversarial network called GARAGE produces realistic synthetic single-cell RNA-seq data that preserves rare cell types and ...

Researchers have developed ProD, a visualizable filter feature selection method that ranks variables by measuring the geometric overlap between class ...

A pilot machine learning study of 20 mother-child dyads found that maternal lactation nutrients such as phosphatidylcholine, glutathione, and glycemic ...

Researchers at Yazd University developed a binary version of the Puma Optimization Algorithm that achieved 91.53 percent classification accuracy and ...

Researchers have adapted a two-stage sparse regression method called uniLasso to the UK Biobank, producing polygenic risk scores that match ...

A new deep learning framework called MedSegNet-AXU segments multiple sclerosis lesions from 3D MRI with a 98.58 percent Dice score ...

Researchers have developed an unsupervised algorithm that uses topological data analysis to detect functional stages in EEG recordings from meditation ...

A benchmarking study in BMC Infectious Diseases shows that data balancing, feature selection, and hyperparameter tuning make machine learning models ...

Researchers in New Delhi have built a hybrid deep learning framework combining improved SMOTE, swarm-based feature selection, and chaos-assisted metaheuristic ...

A new hybrid AI framework combining deep convolutional networks with multi-objective evolutionary optimization achieves 98.5 percent accuracy in assessing vocational ...

A new explainable machine learning framework combining EEG signals with clinical data distinguishes Alzheimer's disease from frontotemporal dementia with 89.8 ...

A new machine learning framework called Seq2DomML predicts residue-level protein domain boundaries in bacterial proteins directly from sequence, outperforming established ...

Researchers in India have developed a multi-phase fusion architecture that identifies stable, consistent features across a writer's genuine signatures, achieving ...

A rough set theory analysis of the METABRIC cohort shows that a compact set of routine clinical variables can moderately ...

A systematic review of 237 studies from 2014 to 2024 maps how explainable AI techniques such as SHAP and LIME ...

In an era where understanding the intricacies of cellular behavior is paramount to advancements in biological sciences, the work conducted ...