Pair Matcher (PaM): fast model-based optimization of treatment/case-control matches | Zendy

Eran Elhaik | Zendy; Desmon̄d Ryan | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Pair Matcher (PaM): fast model-based optimization of treatment/case-control matches

Author(s) -

Eran Elhaik,

Desmon̄d Ryan

Publication year - 2018

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bty946

Subject(s) - population stratification , computer science , pairing , precision medicine , population , a priori and a posteriori , principal component analysis , homogeneous , data mining , artificial intelligence , statistics , machine learning , mathematics , medicine , biology , genetics , philosophy , physics , superconductivity , environmental health , epistemology , quantum mechanics , combinatorics , gene , genotype , single nucleotide polymorphism

In clinical trials, individuals are matched using demographic criteria, paired and then randomly assigned to treatment and control groups to determine a drug's efficacy. A chief cause for the irreproducibility of results across pilot to Phase-III trials is population stratification bias caused by the uneven distribution of ancestries in the treatment and control groups.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research