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

Data Reporting and Recording01:24

Data Reporting and Recording

5.5K
Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
5.5K
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
Electron Orbital Model01:18

Electron Orbital Model

72.3K
Orbitals are the areas outside of the atomic nucleus where electrons are most likely to reside. They are characterized by different energy levels, shapes, and three-dimensional orientations. The location of electrons is described most generally by a shell or principal energy level, then by a subshell within each shell, and finally, by individual orbitals found within the subshells.
The first shell is closest to the nucleus, and it has only one subshell with a single spherical orbital called the...
72.3K
Review and Preview01:10

Review and Preview

8.4K
In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
Percentiles are a type of fractile that partition data into...
8.4K
Review and Preview01:13

Review and Preview

11.5K
Data are individual items of information obtained from a population or sample. Data may be classified as qualitative (categorical), quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample. Random...
11.5K

You might also read

Related Articles

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

Sort by
Same author

Seasonal Variation and Genetic Evaluation of Needle Catechin Content in Half-Sib Families of <i>Pinus taeda</i>.

Plants (Basel, Switzerland)·2026
Same author

Realistic PET image synthesis from MRI for automated inference of brain atrophy and Alzheimer's.

iScience·2026
Same author

Deep Continuous-Time State-Space Models for Marked Event Sequences.

Advances in neural information processing systems·2026
Same author

Activity of Nonhallucinogenic Ibogalogs on Chemotherapy-Induced Peripheral Neuropathic Pain in Mice.

ACS chemical neuroscience·2026
Same author

Transcriptome-Based Dissection of the Molecular Mechanisms Underlying Flooding Stress Responses of Eastern Cottonwood in the Floodplains of the Middle and Lower Reaches of the Yangtze River.

Plants (Basel, Switzerland)·2026
Same author

A Survey on Unifying Large Language Models and Knowledge Graphs for Biomedicine and Healthcare.

KDD : proceedings. International Conference on Knowledge Discovery & Data Mining·2026

Related Experiment Video

Updated: Feb 9, 2026

Deep Learning-Based Segmentation of Cryo-Electron Tomograms
10:25

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Published on: November 11, 2022

10.9K

Opportunities and challenges in developing deep learning models using electronic health records data: a systematic

Cao Xiao1, Edward Choi2, Jimeng Sun2

  • 1AI for Healthcare, IBM Research, Cambridge, Massachusetts, USA.

Journal of the American Medical Informatics Association : JAMIA
|June 13, 2018
PubMed
Summary

Deep learning models show promise for analyzing electronic health record (EHR) data in healthcare. Further research is needed to address challenges in data availability, model interpretability, and deployment for clinical use.

More Related Videos

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
A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

4.5K

Related Experiment Videos

Last Updated: Feb 9, 2026

Deep Learning-Based Segmentation of Cryo-Electron Tomograms
10:25

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Published on: November 11, 2022

10.9K
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
A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

4.5K

Area of Science:

  • Medical Informatics
  • Artificial Intelligence in Healthcare

Background:

  • Electronic Health Records (EHRs) contain vast amounts of patient data.
  • Deep learning (DL) offers powerful tools for analyzing complex health data.

Purpose of the Study:

  • To systematically review deep learning models applied to EHR data.
  • To illustrate DL architectures, applications, and challenges in health analytics.
  • To identify future research directions in EHR data analysis.

Main Methods:

  • Systematic literature search of PubMed and Google Scholar (2010-2018).
  • Analysis of 98 selected articles based on analytics tasks, DL architectures, data challenges, and evaluation strategies.

Main Results:

  • Identified key analytics tasks: disease detection, event prediction, concept embedding, data augmentation, and privacy.
  • Summarized the application of various deep learning architectures to these tasks.
  • Discussed challenges specific to EHR data, including data quality, interpretability, and deployment.

Conclusions:

  • Deep learning has achieved early success in health analytics using EHR data.
  • Key challenges remain, including data/label availability, model interpretability, transparency, and ease of deployment.