Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Purpose of Health Records I01:11

Purpose of Health Records I

1.8K
The vital purpose of health records is to provide a complete and accurate account of a patient's medical history, including communication, diagnostic and therapeutic orders, care planning, research, and quality review.
Here's a breakdown of how health records serve these purposes:
1.8K
Purpose of Health Records II01:19

Purpose of Health Records II

1.4K
Health records serve various essential purposes in the healthcare system. Here are some key purposes:
1.4K
Bioequivalence of Drugs: Drugs with Multiple Indications01:09

Bioequivalence of Drugs: Drugs with Multiple Indications

158
The concept of therapeutic equivalence (TE) in drugs with multiple indications is complex. A generic drug may be therapeutically equivalent to a brand-name product for one specific indication, but this doesn't necessarily mean it's equivalent for all other indications. Evidence of TE in one patient group and bioequivalence shown in healthy volunteers can support—but not confirm—TE for other indications. However, definitive proof requires individual clinical studies for each...
158
Indicators02:39

Indicators

60.6K
Certain organic substances change color in dilute solution when the hydronium ion concentration reaches a particular value. For example, phenolphthalein is a colorless substance in any aqueous solution with a hydronium ion concentration greater than 5.0 × 10−9 M (pH < 8.3). In more basic solutions where the hydronium ion concentration is less than 5.0 × 10−9 M (pH > 8.3), it is red or pink. Substances such as phenolphthalein, which can be used to determine the pH of a solution, are...
60.6K
Overview of Biostatistics in Health Sciences01:19

Overview of Biostatistics in Health Sciences

5.2K
Biostatistics involves the application of statistical techniques to scientific research in health-related fields, including biology and public health. These techniques are essential for designing studies, collecting data, and analyzing it to draw meaningful conclusions. Given the complexity of biological processes, particularly in studies involving human subjects, biostatistical methods are crucial for effectively organizing and interpreting data that might otherwise obscure underlying patterns...
5.2K
Overview of Electron Microscopy01:25

Overview of Electron Microscopy

14.5K
The wavelengths of visible light ultimately limit the maximum theoretical resolution of images created by light microscopes. Most light microscopes can only magnify 1000X, and a few can magnify up to 1500X. Electrons, like electromagnetic radiation, can behave like waves, but with wavelengths of 0.005 nm, they produce significantly greater resolution up to 0.05 nm as compared to 500 nm for visible light. An electron microscope (EM) can create a sharp image that is magnified up to 2,000,000X.
14.5K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Rule-Based Algorithm to Identify Recurrent Non-Hodgkin Lymphoma in Electronic Health Data.

JCO clinical cancer informatics·2026
Same author

Deep learning enabled decision support systems in epilepsy surgery: a scoping review.

npj health systems·2026
Same author

Environmental and social determinants of health enhance machine learning models for pneumonia readmission.

Digital health·2026
Same author

Experimental Study of YaJieShaBa Antialcoholic Hepatic Fibrosis Through TGF-β1/Smad Signaling Pathway.

Mediators of inflammation·2026
Same author

Mechanistic Insights into the Anti-Constipation Potential of Zeng Ye Tang Compound: UHPLC-Q-TOF MS/MS, Network Pharmacology, and In vivo Experimental Validation.

Combinatorial chemistry & high throughput screening·2026
Same author

Evaluating model generalizability for suicide attempt risk prediction: traditional machine vs deep learning.

Npj mental health research·2026

Related Experiment Video

Updated: Jan 30, 2026

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients
09:00

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients

Published on: April 13, 2021

5.3K

Overview of the First Natural Language Processing Challenge for Extracting Medication, Indication, and Adverse Drug

Abhyuday Jagannatha1, Feifan Liu2, Weisong Liu3,4

  • 1College of Information and Computer Sciences, University of Massachusetts, Amherst, MA, USA.

Drug Safety
|January 17, 2019
PubMed
Summary

The Medication and Adverse Drug Events (MADE 1.0) corpus and challenge advanced natural language processing (NLP) for electronic health records. NLP models showed significant progress in identifying medications and adverse drug events, though joint tasks require further development.

More Related Videos

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
09:27

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

10.7K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

8.1K

Related Experiment Videos

Last Updated: Jan 30, 2026

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients
09:00

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients

Published on: April 13, 2021

5.3K
Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
09:27

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

10.7K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

8.1K

Area of Science:

  • Biomedical Informatics
  • Clinical Natural Language Processing
  • Pharmacovigilance

Background:

  • Electronic Health Records (EHRs) contain valuable data for drug safety surveillance.
  • Extracting medication and adverse drug event (ADE) information from EHRs is crucial for pharmacovigilance.
  • Standardized evaluation tasks are needed to advance NLP in the clinical domain.

Purpose of the Study:

  • To introduce the Medication and Adverse Drug Events (MADE 1.0) corpus and the 2018 challenge.
  • To establish benchmarks for NLP systems applied to EHR data for drug safety.
  • To assess the state-of-the-art in extracting medication, indication, and ADE information from clinical notes.

Main Methods:

  • Development of the MADE 1.0 corpus: 1089 de-identified EHR notes from cancer patients.
  • Design of three shared NLP tasks: Named Entity Recognition (NER), Relation Identification (RI), and joint NER-RI.
  • Evaluation of 11 participating teams' NLP system submissions.

Main Results:

  • The best systems achieved F1 scores of 0.82 for NER, 0.86 for RI, and 0.61 for NER-RI.
  • Ensemble methods further improved performance to 0.85 (NER), 0.87 (RI), and 0.66 (NER-RI).
  • Significant progress was observed in clinical NLP tasks for drug safety.

Conclusions:

  • Recent NLP advancements have markedly improved medication and ADE extraction from EHRs.
  • The MADE 1.0 challenge provided valuable benchmarks for clinical NLP.
  • Further research is needed to enhance performance on joint NER-RI tasks in clinical text.