RxNorm: prescription for electronic drug information exchange

By Simon Liu, Wei Ma, Robin Moore, V. Ganesan, S. J. Nelson. 2005

292 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Health Information Management, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Zexian Zeng
2. Tristan Naumann
3. Xiaoyu Li
4. Yu Deng
5. Yuan Luo

In Health Information Management

1. Yuan Luo
2. Xiaoyu Li
3. Yu Deng
4. Zexian Zeng
5. Tristan Naumann

In Molecular Biology

1. Zexian Zeng
2. Tristan Naumann
3. Xiaoyu Li
4. Yu Deng
5. Yuan Luo

Citations in the corpus

• Natural Language Processing for EHR-Based Computational Phenotyping (2018, background): “Many of these studies relied heavily on structured and coded patient data; for example, using encodings such as International Classification of Disease, 9th Revision (ICD-9) [4], its successor the 10th Revision (ICD-10) [5], Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) [6], RxNor”
• Normalized names for clinical drugs: RxNorm at 6 years (2011, methodology): “Source content is integrated into RxNorm through an inversion, insertion, editing, and production life cycle.(23) First, content from source vocabularies is converted to a common format which can be processed by the RxNorm system.”