Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Lung cancer prediction using neural network ensemble with histogram of oriented gradient genomic features.

TheScientificWorldJournal - 1 Jan 2015

Adetiba Emmanuel, Olugbara Oludayo O

Abstract excerpt

This paper reports an experimental comparison of artificial neural network (ANN) and support vector machine (SVM) ensembles and their "nonensemble" variants for lung cancer prediction. These machine learning classifiers were trained to predict lung cancer using samples of patient nucleotides with...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Biomarkers, Tumor
Share to Carcinoma, Non-Small-Cell Lung
Share to ErbB Receptors

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Lung Neoplasms

Share to Neural Networks, Computer

Share to Proto-Oncogene Proteins p21(ras)

Share to Support Vector Machine

Share to Tumor Suppressor Protein p53

Source

Open in PubMed Open full text

Identifiers

PMID: 25802891
DOI: 10.1155/2015/786013
PMCID: PMC4352926

Genes

LBP

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 4 Sept 2026. Prepared record publication-25802891-2026-09-04.2. Manifest publication-graph-cohort-2026-09-04.2.

Source receipt: PubMed via Helena Literature Corpus, retrieved 4 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Lung cancer prediction using neural network ensemble with histogram of oriented gradient genomic features.PMID 25802891Read ↗

Improved Classification of Lung Cancer Using Radial Basis Function Neural Network with Affine Transforms of Voss Representation.Semantic proximity Read ↗

Advancing Lung Cancer Classification through Machine Learning: A Comprehensive Comparative Analysis of Model PerformanceSemantic proximity Read ↗

On the way for the best imaging features from CT images to predict EGFR Mutation Status in Lung Cancer.Semantic proximity Read ↗

Ensemble Strategies for EGFR Mutation Status Prediction in Lung Cancer.Semantic proximity Read ↗

A Radiogenomics Ensemble to Predict EGFR and KRAS Mutations in NSCLC.Semantic proximity Read ↗

Disease prediction model: An efficient machine learning- based DNA classifierSemantic proximity Read ↗

A normalized differential sequence feature encoding method based on amino acid sequencesSemantic proximity Read ↗

Prediction of EGFR Mutation Status in Non–Small Cell Lung Cancer Based on Ensemble LearningSemantic proximity Read ↗

DEL-Thyroid: deep ensemble learning framework for detection of thyroid cancer progression through genomic mutation.Semantic proximity Read ↗

Lung cancer prediction from microarray data by gene expression programmingSemantic proximity Read ↗

Computer-Aided Diagnosis of Lung Nodules in Computed Tomography by Using Phylogenetic Diversity, Genetic Algorithm, and SVM.Semantic proximity Read ↗

A Novel Algorithm for Histopathological Lung Cancer DetectionSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.