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

Validation of a multigenic model to predict seizure control in newly treated epilepsy.

Epilepsy research - 1 Dec 2014

Shazadi Kanvel, Petrovski Slavé, Roten Annie, Miller Hugh, Huggins Richard M, Brodie Martin J, Pirmohamed Munir, Johnson Michael R, Marson Anthony G, O'Brien Terence J, Sills Graeme J

Abstract excerpt

A multigenic classifier based on five single nucleotide polymorphisms (SNPs) was previously reported to predict treatment response in an Australian newly-diagnosed epilepsy cohort using a k-nearest neighbour (kNN) algorithm. We assessed the validity of this classifier in predicting response to initial antiepileptic drug (AED) treatment in two UK cohorts of newly-diagnosed epilepsy and investigated the utility of...

Read the complete abstract on PubMed

Topics

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

Share to Anticonvulsants
Share to Artificial Intelligence

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Biomarkers, Pharmacological

Share to Carbamazepine

Share to Lamotrigine

Share to Seizures

Share to Triazines

Share to Valproic Acid

Source

Identifiers

PMID: 25282706
DOI: 10.1016/j.eplepsyres.2014.08.022

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 11 closest

Validation of a multigenic model to predict seizure control in newly treated epilepsy.PMID 25282706Read ↗

Multi-SNP pharmacogenomic classifier is superior to single-SNP models for predicting drug outcome in complex diseases.Semantic proximity Read ↗

Biomarkers for treatment outcome in newly diagnosed epilepsySemantic proximity Read ↗

Utilizing Machine Learning Algorithms to Predict Subject Genetic Mutation Class from In Silico Models of Neuronal NetworksSemantic proximity Read ↗

Genetic predictors for epilepsy development, treatment response and dosingSemantic proximity Read ↗

Aggregated Three Genetic Biomarkers in Idiopathic Generalized Epilepsy with Artificial Neural NetworkSemantic proximity Read ↗

SCN1A, SCN2A and SCN3A gene polymorphisms and responsiveness to antiepileptic drugs: a multicenter cohort study and meta-analysis.Semantic proximity Read ↗

Identifying a predictive model for response to atypical antipsychotic monotherapy treatment in south Indian schizophrenia patients.Semantic proximity Read ↗

Gene-to-gene interaction between sodium channel-related genes in determining the risk of antiepileptic drug resistance.Semantic proximity Read ↗

SCN1A variations and response to multiple antiepileptic drugs.Semantic proximity Read ↗

The association between polymorphisms in RLIP76 and drug response in epilepsy.Semantic proximity Read ↗

Multidrug-resistant genotype (ABCB1) and seizure recurrence in newly treated epilepsy: data from international pharmacogenetic cohorts.Semantic proximity Read ↗

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