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

Decision Making: P-value Method01:09

Decision Making: P-value Method

6.8K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
6.8K
Methods of Documentation II: POMR01:26

Methods of Documentation II: POMR

1.3K
The Problem-Oriented Medical Record (POMR) revolutionized medical record-keeping by introducing a systematic approach focusing on the patient's problems rather than merely listing symptoms. Dr. Lawrence Weed's introduction of this method in the 1960s marked a significant advancement in medical documentation. The POMR framework consists of four key components: the database, problem list, plan of care, and progress notes.
1.3K
Heuristics01:21

Heuristics

598
Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
598
Methods of Documentation III: PIE01:21

Methods of Documentation III: PIE

2.0K
Problem-intervention-evaluation (PIE) is a systematic approach to documentation used in healthcare settings for clinical decision-making and patient care planning. It is a structured approach to organizing patient data based on problems, interventions, and evaluations. Here's a breakdown of its key features and considerations:
2.0K
The Representativeness Heuristic02:13

The Representativeness Heuristic

16.6K
The representative heuristic describes a biased way of thinking, in which you unintentionally stereotype someone or something. For example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.
16.6K

You might also read

Related Articles

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

Sort by
Same author

Interpretable EEG biomarkers for neurological disease models in mice using bag-of-waves classifiers.

bioRxiv : the preprint server for biology·2025
Same author

Latent Growth Models of Longitudinal Changes in Functional Connectivity during Early Stage Psychosis.

Neuroinformatics·2025
Same author

A Machine Learning Model for Post-Concussion Musculoskeletal Injury Risk in Collegiate Athletes.

Sports medicine (Auckland, N.Z.)·2025
Same author

A Machine Learning Model for Post-Concussion Musculoskeletal Injury Risk in Collegiate Athletes.

medRxiv : the preprint server for health sciences·2025
Same author

MRI-based whole-brain elastography and volumetric measurements to predict brain age.

Biology methods & protocols·2025
Same author

Uncovering key predictive channels and clinical variables in the gamma band auditory steady-state response in early-stage psychosis: a longitudinal study.

Acta neuropsychiatrica·2024
Same journal

Classification of periapical radiographic findings for root canal therapy decision support using deep neural networks.

BMC medical informatics and decision making·2026
Same journal

Machine learning-based risk assessment of neonatal perinatal adverse outcomes of anemia during pregnancy: a modeling study.

BMC medical informatics and decision making·2026
Same journal

Intelligent differentiation between Parkinson's disease and essential tremor using wearable sensors and machine learning: a temporal validation study.

BMC medical informatics and decision making·2026
Same journal

Risk prediction of sepsis-associated acute kidney injury: development, validation of a machine learning model with multicenter data.

BMC medical informatics and decision making·2026
Same journal

Trajectory analysis of sleep disorders and anxiety-depression in female breast cancer patients undergoing chemotherapy: based on group-based Multi-Trajectory Model and machine learning.

BMC medical informatics and decision making·2026
Same journal

Multitask learning of longitudinal circulating biomarkers and clinical outcomes: identification of optimal machine-learning and deep-learning models.

BMC medical informatics and decision making·2026
See all related articles

Related Experiment Video

Updated: Jan 2, 2026

Generalized Psychophysiological Interaction PPI Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease
09:38

Generalized Psychophysiological Interaction PPI Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease

Published on: November 14, 2017

15.5K

Improving reference prioritisation with PICO recognition.

Austin J Brockmeier1,2, Meizhi Ju1, Piotr Przybyła1,3

  • 1National Centre of Text Mining, School of Computer Science, University of Manchester, Princess Street, Manchester, M1 7DN, UK.

BMC Medical Informatics and Decision Making
|December 7, 2019
PubMed
Summary
This summary is machine-generated.

Machine learning models enhanced with PICO (patient/population, intervention, comparator, outcomes) features improve systematic review screening. This approach aids in identifying relevant studies and extracting key information more efficiently.

Keywords:
Active learningEvidence-based medicineLogistic regressionMachine learningSystematic reviewText mining

More Related Videos

Primer Extension Capture: Targeted Sequence Retrieval from Heavily Degraded DNA Sources
15:28

Primer Extension Capture: Targeted Sequence Retrieval from Heavily Degraded DNA Sources

Published on: September 3, 2009

20.7K
Topographical Estimation of Visual Population Receptive Fields by fMRI
06:02

Topographical Estimation of Visual Population Receptive Fields by fMRI

Published on: February 3, 2015

9.6K

Related Experiment Videos

Last Updated: Jan 2, 2026

Generalized Psychophysiological Interaction PPI Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease
09:38

Generalized Psychophysiological Interaction PPI Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease

Published on: November 14, 2017

15.5K
Primer Extension Capture: Targeted Sequence Retrieval from Heavily Degraded DNA Sources
15:28

Primer Extension Capture: Targeted Sequence Retrieval from Heavily Degraded DNA Sources

Published on: September 3, 2009

20.7K
Topographical Estimation of Visual Population Receptive Fields by fMRI
06:02

Topographical Estimation of Visual Population Receptive Fields by fMRI

Published on: February 3, 2015

9.6K

Area of Science:

  • Biomedical Informatics
  • Computational Linguistics
  • Evidence Synthesis

Background:

  • Machine learning (ML) aids systematic reviews by automating reference retrieval and information extraction.
  • Named entity recognition (NER) is crucial for identifying study characteristics like PICO (patient/population, intervention, comparator, outcomes).

Purpose of the Study:

  • To develop and evaluate an ML model incorporating PICO features for enhanced systematic review screening.
  • To assess the impact of PICO-tagged features on the relevancy classification of biomedical abstracts.

Main Methods:

  • Trained a recurrent neural network NER model on a PICO-annotated biomedical abstract corpus.
  • Applied the NER model to abstracts from systematic reviews and used PICO tags as features for a relevancy classification model.
  • Evaluated performance gains using simulations and statistical significance tests.

Main Results:

  • Incorporating PICO features improved performance metrics in 15 out of 20 tested collections.
  • Substantial performance gains were observed in specific systematic reviews.
  • Analysis identified specific words within PICO contexts that are highly indicative of relevance.

Conclusions:

  • PICO-tagged words within abstracts serve as predictive features for study inclusion.
  • Integrating PICO annotation models into relevancy classification pipelines shows promise for systematic reviews.
  • PICO annotations can directly assist users in data extraction and semantic search.