Literature DB >> 33324002

Desiderata for delivering NLP to accelerate healthcare AI advancement and a Mayo Clinic NLP-as-a-service implementation.

Andrew Wen1, Sunyang Fu1, Sungrim Moon1, Mohamed El Wazir2, Andrew Rosenbaum2, Vinod C Kaggal3, Sijia Liu1, Sunghwan Sohn1, Hongfang Liu4, Jungwei Fan5.   

Abstract

Data is foundational to high-quality artificial intelligence (AI). Given that a substantial amount of clinically relevant information is embedded in unstructured data, natural language processing (NLP) plays an essential role in extracting valuable information that can benefit decision making, administration reporting, and research. Here, we share several desiderata pertaining to development and usage of NLP systems, derived from two decades of experience implementing clinical NLP at the Mayo Clinic, to inform the healthcare AI community. Using a framework, we developed as an example implementation, the desiderata emphasize the importance of a user-friendly platform, efficient collection of domain expert inputs, seamless integration with clinical data, and a highly scalable computing infrastructure.

Year:  2019        PMID: 33324002     DOI: 10.1038/s41746-019-0208-8

Source DB:  PubMed          Journal:  NPJ Digit Med        ISSN: 2398-6352


  3 in total

1.  Big data in healthcare - the promises, challenges and opportunities from a research perspective: A case study with a model database.

Authors:  Mohammad Adibuzzaman; Poching DeLaurentis; Jennifer Hill; Brian D Benneyworth
Journal:  AMIA Annu Symp Proc       Date:  2018-04-16

2.  A hadoop-based method to predict potential effective drug combination.

Authors:  Yifan Sun; Yi Xiong; Qian Xu; Dongqing Wei
Journal:  Biomed Res Int       Date:  2014-07-23       Impact factor: 3.411

3.  Populating Physician Biographical Pages Based on EMR Data.

Authors:  Feichen Shen; Sunghwan Sohn; Majid Rastegar-Mojarad; Sijia Liu; Joshua J Pankratz; Michael A Hatton; Nancy Sowada; Om K Shrestha; Shawna L Shurson; Hongfang Liu
Journal:  AMIA Jt Summits Transl Sci Proc       Date:  2017-07-26
  3 in total

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