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Ontology-based literature mining and class effect analysis of adverse drug reactions associated with neuropathy-inducing drugs.

Author: HeYongqun, HurJunguk, ÖzgürArzucan

Journal ArticleAn article published in an academic or professional journal that reports original research or scholarly analysis.
Research Support, Non-U.S. Gov'tResearch funding provided by government agencies outside the United States.

Overview

This study aimed to develop a system to identify adverse drug reactions (ADRs) like peripheral neuropathy from drug labels and understand their mechanisms, particularly for over 240 drugs previously identified as potential neuropathy-inducing agents.
Paper Details　
Original Abstract of the Article :
Adverse drug reactions (ADRs), also called as drug adverse events (AEs), are reported in the FDA drug labels; however, it is a big challenge to properly retrieve and analyze the ADRs and their potential relationships from textual data. Previously, we identified and ontologically modeled over 240 dru...See full text at original site
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引用元：
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5991464/

データ提供：米国国立医学図書館（NLM）

Neuropathy-Inducing Drugs: Mapping the Desert of Adverse Drug Reactions

Neuropathy-inducing drugs (NIDs), like a hidden sandstorm, can have unexpected and potentially harmful effects on the nervous system. This research focuses on developing an ontology-based literature mining system to identify and analyze adverse drug reactions (ADRs) associated with NIDs, particularly those related to peripheral neuropathy.

NIDs: A Desert of Data

The study employed an ontology-based approach to mine drug labels and other relevant literature to identify ADRs associated with NIDs. This approach allowed the researchers to systematically identify and analyze potential mechanisms of action for these drugs, providing valuable insights into their adverse effects.

NIDs: A Desert Oasis of Knowledge

This research underscores the importance of understanding the potential ADRs associated with NIDs. By using an ontology-based approach to mine literature, researchers can gain a deeper understanding of these adverse effects and develop strategies to minimize their occurrence.

Dr. Camel's Conclusion

This study demonstrates the power of ontology-based literature mining in identifying and analyzing ADRs associated with NIDs. It emphasizes the importance of using data-driven approaches to better understand the potential risks and benefits of medications and improve patient safety.
Date :
  1. Date Completed 2019-07-31
  2. Date Revised 2019-07-31
Further Info :

Pubmed ID

29880031

DOI: Digital Object Identifier

PMC5991464

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Languages

English

Positive IndicatorAn AI analysis index that serves as a benchmark for how positive the results of the study are. Note that it is a benchmark and requires careful interpretation and consideration of different perspectives.

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