A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is
The motivation for this research comes from the gap found in discovering the common ground for medical context learning through analytics for different purposes of diagnosing, recommending, prescribing or treating patients for uniform phenotype features from patients' profile. Authors of this paper while searching for possible solutions for medical context learning found that unified corpora tagged with medical nomenclature was missing to train the analytics for medical context learning.doi:10.37965/jait.2022.0127 fatcat:5orjqct5anhjdg7sr54rwmyqjm