Extracting Medical Concepts from Medical Social Media with Clinical NLP Tools: A Qualitative Study

نویسنده

  • Kerstin Denecke
چکیده

Medical social-media provides a rich source of information on diagnoses, treatment and experiences. For its automatic analysis, tools need to be available that are able to process this particular data. Since content and language of medical social-media differs from those of general social media and of clinical document, additional methods are necessary in particular to identify medical concepts and relations among them. In this paper, we analyse the quality of two existing tools for extracting clinical terms from natural language that were originally developed for processing clinical documents (cTakes, MetaMap) by applying them on a real-world set of medical blog postings. The results show that medical concepts that are explicitly mentioned in texts can reliably be extracted by those tools also frommedical social-media data, but the extraction misses relevant information captured in paraphrase or formulated in common language.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Knowledge Author: facilitating user-driven, domain content development to support clinical information extraction

BACKGROUND Clinical Natural Language Processing (NLP) systems require a semantic schema comprised of domain-specific concepts, their lexical variants, and associated modifiers to accurately extract information from clinical texts. An NLP system leverages this schema to structure concepts and extract meaning from the free texts. In the clinical domain, creating a semantic schema typically requir...

متن کامل

Extracting Concepts Related to a Homelessness from the Free Text of VA Electronic Medical Records

Mining the free text of electronic medical records (EMR) using natural language processing (NLP) is an effective method of extracting information not always captured in administrative data. We sought to determine if concepts related to homelessness, a non-medical condition, were amenable to extraction from the EMR of Veterans Affairs (VA) medical records. As there were no off-the-shelf products...

متن کامل

A Survey of Librarians' Perspectives on Marketing Library Services Using Social Media in Tehran, Iran, and Shahid Beheshti Universities of Medical Sciences

Background and Aim: The present study has examined librarians' views on the marketing of library services using social media as well as the applications, benefits, and challenges of their use in Tehran, Iran, and Shahid Beheshti Universities of Medical Sciences.  Materials and Methods: This research was a descriptive and applied survey and was conducted in 2019. The data collection tool was a ...

متن کامل

Aspiring to Unintended Consequences of Natural Language Processing: A Review of Recent Developments in Clinical and Consumer-Generated Text Processing.

OBJECTIVES This paper reviews work over the past two years in Natural Language Processing (NLP) applied to clinical and consumer-generated texts. METHODS We included any application or methodological publication that leverages text to facilitate healthcare and address the health-related needs of consumers and populations. RESULTS Many important developments in clinical text processing, both...

متن کامل

v3NLP Framework: Tools to Build Applications for Extracting Concepts from Clinical Text

INTRODUCTION Substantial amounts of clinically significant information are contained only within the narrative of the clinical notes in electronic medical records. The v3NLP Framework is a set of "best-of-breed" functionalities developed to transform this information into structured data for use in quality improvement, research, population health surveillance, and decision support. BACKGROUND...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014