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

Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

4.0K
An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
4.0K
The Evidence for Evolution02:55

The Evidence for Evolution

40.1K
Genetic variations accumulating within populations over generations give rise to biological evolution. Evolutionary changes can result in the formation of novel varieties and entire new species. These changes are responsible for the diverse forms of life inhabiting the planet. The evidence for evolution suggests that all living organisms descended from common ancestors.
40.1K
Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

376
Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
376
Natural and Artificial Concepts01:24

Natural and Artificial Concepts

740
In psychology, concepts can be divided into two categories: natural and artificial. Natural concepts are formed through direct or indirect experiences. For example, consider the concept of snow. If you live in a place with regular snowfall, such as Essex Junction, Vermont, you know snow through direct experiences. You’ve seen it fall, touched it, shoveled it, and played in it. You recognize its texture, appearance, and even its smell. In contrast, if you live on an island like Saint...
740
Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

6.5K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
6.5K
Cause and Effect01:53

Cause and Effect

10.5K
While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable, is actually causing the systematic movement in our variables of interest. For instance, as sales in ice cream increase, so does the overall rate of crime. Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone?
10.5K

You might also read

Related Articles

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

Sort by
Same author

Deception in clinical large language models: an under-recognised safety risk.

The Lancet. Digital health·2026
Same author

Age and seasonality in Hirschsprung-associated enterocolitis risk: a longitudinal cohort study.

Pediatric surgery international·2026
Same author

Impact of Exposure Parameters on Deep Learning Models in Chest Radiography and Implications for Deployment.

Radiology. Artificial intelligence·2026
Same author

BRIDGE: benchmarking large language models for understanding real-world clinical practice texts.

Nature biomedical engineering·2026
Same author

An evidence gap map of digital health interventions for enhancing patient engagement in healthcare.

NPJ digital medicine·2026
Same author

Discriminating HFrEF vs HFpEF from chest radiographs: Mitigating demographic performance gaps via augmentation and multimodal fusion.

PLOS digital health·2026
Same journal

Estimated preventable fraction of chronic disease attributed to long-term physical activity and diet quality, independent of body weight: a prospective cohort study of three US cohorts.

Lancet regional health. Americas·2026
Same journal

Delivering cervical cancer screening and management to women in remote communities of the Peruvian Amazon: a mixed methods analysis of a mobile point-of-care intervention.

Lancet regional health. Americas·2026
Same journal

Blood donor serosurveys and national dengue burden estimates in Argentina.

Lancet regional health. Americas·2026
Same journal

Developmental predictors of suicide attempts from childhood to early adulthood: a 15-year prospective cohort study.

Lancet regional health. Americas·2026
Same journal

Chikungunya resurgence highlights gaps in <i>Aedes</i> surveillance and control in South America.

Lancet regional health. Americas·2026
Same journal

Food-environment policies for child nutrition in Ecuador and Latin America: beyond front-of-package labels and advertising restrictions.

Lancet regional health. Americas·2026
See all related articles

Related Experiment Video

Updated: May 1, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

1.9K

When evidence meets artificial intelligence.

Gustavo Adolfo Cruz-Suarez1,2,3, Daniela Hincapié-Ayala1, Felipe Ocampo Osorio1,2

  • 1Centro de Investigaciones Clínicas, Unidad de Inteligencia Artificial, Fundación Valle del Lili, Cali, Valle del Cauca, 760032, Colombia.

Lancet Regional Health. Americas
|April 30, 2026
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) enhances evidence-based medicine (EBM) by integrating diverse data, but requires careful epidemiologic design. Its effective implementation necessitates addressing health system inequities and ensuring transparent validation for true clinical benefit.

Keywords:
Artificial intelligenceBig dataEvidence-based medicineInterpretabilityMachine learning

More Related Videos

Artificial Intelligence Approaches to Assessing Primary Cilia
08:58

Artificial Intelligence Approaches to Assessing Primary Cilia

Published on: May 1, 2021

3.9K
Automation of the Micronucleus Assay Using Imaging Flow Cytometry and Artificial Intelligence
09:11

Automation of the Micronucleus Assay Using Imaging Flow Cytometry and Artificial Intelligence

Published on: January 27, 2023

2.9K

Related Experiment Videos

Last Updated: May 1, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

1.9K
Artificial Intelligence Approaches to Assessing Primary Cilia
08:58

Artificial Intelligence Approaches to Assessing Primary Cilia

Published on: May 1, 2021

3.9K
Automation of the Micronucleus Assay Using Imaging Flow Cytometry and Artificial Intelligence
09:11

Automation of the Micronucleus Assay Using Imaging Flow Cytometry and Artificial Intelligence

Published on: January 27, 2023

2.9K

Area of Science:

  • Health Informatics
  • Epidemiology
  • Artificial Intelligence in Medicine

Background:

  • Classical evidence-based medicine (EBM) faces challenges with modern health system complexity and data scale.
  • Biomedical data growth positions artificial intelligence (AI) as a complementary tool for evidence generation, not a replacement for epidemiological reasoning.

Purpose of the Study:

  • To review how AI is transforming the methodological and ethical underpinnings of EBM.
  • To explore AI's role in multimodal data integration, target trial emulation, and simulation-based modeling within EBM.

Main Methods:

  • State-of-the-art review of AI applications in EBM.
  • Analysis of AI's impact on evidence generation, causal validity, and clinical benefit.
  • Examination of implementation factors including epidemiologic design and human-machine collaboration.

Main Results:

  • AI reshapes EBM through multimodal data integration, target trial emulation, and simulation.
  • Predictive performance of AI does not automatically guarantee causal validity or clinical utility.
  • Implementation challenges include fragmented health systems, digital infrastructure disparities, and the need for robust epidemiologic design.

Conclusions:

  • AI's constructive role in EBM requires more than technological advancement; it demands governance reform, transparent validation, and structural changes.
  • Equitable deployment of AI in healthcare is constrained by fragmented systems and uneven digital infrastructure, risking the reinforcement of existing inequities.
  • Successful integration of AI into EBM hinges on rigorous design, seamless clinical informatics integration, and effective human-machine collaboration to ensure clinical benefit and validity.