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

Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

6.1K
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...
6.1K
Ethical Standards I01:25

Ethical Standards I

1.4K
The American Nurses Association (ANA) created and implemented the first nationally accepted Code of Ethics for Nurses with Interpretive Statements. The Code of Ethics is a living document regularly updated by the ANA and establishes an ethical standard that is non-negotiable for nurses in all roles and settings.
The Code of Ethics provisions outline the nurse's duty to the patient, the healthcare team, the profession, and society. The Code's fundamental principles include advocacy,...
1.4K
Current Trends in Nursing II01:30

Current Trends in Nursing II

3.3K
Trends in nursing are multifactorial and associated with changes in society, within the nursing profession, and in other professions. Notably, telehealth and remote nursing contribute to successful healthcare delivery for numerous patients and help reduce stress for nurses due to nursing shortages. Nurses can reach patients, monitor their conditions, and interact with them using computers, audio, visual accessories, and telephones—for example, remote patient monitoring systems. Likewise,...
3.3K
Health Information Technology and Healthcare Information System01:30

Health Information Technology and Healthcare Information System

3.2K
Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
3.2K
Ethical Dilemmas I01:17

Ethical Dilemmas I

1.7K
Ethical dilemmas in nursing are of utmost importance, as they often arise from the tension between adhering to core ethical principles and the practical realities of healthcare delivery. These dilemmas require nurses to navigate complex situations where competing ethical considerations pull them in different directions.
Let us explore some examples to understand the potentially complex moral decisions nurses face.
Take the case of caring for minors, particularly in areas related to reproductive...
1.7K
Ethical Standards II01:23

Ethical Standards II

1.2K
Ethical standards are the backbone of nursing practice, guiding nurses as they interact with patients, families, and colleagues. These standards are crucial for providing safe, empathetic care centered on the patient's needs.
Nurses are entrusted with upholding various ethical principles and standards. Nurses forge solid therapeutic relationships using trust, empathy, autonomy, confidentiality, and professional competence.
Confidentiality is crucial, embodying respect for individual privacy...
1.2K

You might also read

Related Articles

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

Sort by
Same author

Development and validation of a near-comprehensive RxNorm valueset of opioid medications.

JAMIA open·2026
Same author

What do LLMs value? An evaluation framework for revealing subjective trade-offs in assessment of glycemic control.

Proceedings of machine learning research·2026
Same author

Trends in Suicide Mortality by Method among US Individuals aged 10-24 Years from 1999 to 2024.

medRxiv : the preprint server for health sciences·2026
Same author

What FDA Clearance Does, and Does Not, Mean for Artificial Intelligence.

Annals of internal medicine·2026
Same author

Representation learning to advance multi-institutional studies with electronic health record data from US and France.

Nature communications·2026
Same author

Artificial intelligence for interpreting diabetes data using clinician-curated benchmarks.

The lancet. Diabetes & endocrinology·2026

Related Experiment Video

Updated: Dec 24, 2025

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

1.1K

Machine intelligence in healthcare-perspectives on trustworthiness, explainability, usability, and transparency.

Christine M Cutillo1, Karlie R Sharma1, Luca Foschini2

  • 11National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD USA.

NPJ Digital Medicine
|April 8, 2020
PubMed
Summary

Machine Intelligence (MI) offers significant potential in healthcare, from diagnostics to precision medicine. Addressing challenges like data quality and bias is crucial for ethical and effective implementation in patient care.

Keywords:
DiagnosisDisease preventionMedical imagingPublic healthTherapeutics

More Related Videos

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

922

Related Experiment Videos

Last Updated: Dec 24, 2025

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

1.1K
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

922

Area of Science:

  • Biomedical research
  • Clinical applications
  • Healthcare innovation

Background:

  • Machine Intelligence (MI) is increasingly vital in biomedical discovery, clinical research, diagnostics, and precision medicine.
  • MI tools enhance decision-making for researchers, physicians, and patients, improving health outcomes.
  • The integration of MI in healthcare settings promises to boost efficiency and patient care quality.

Purpose of the Study:

  • To address challenges arising from the growing use of MI in clinical settings.
  • To identify key issues and propose solutions for advancing MI in healthcare.
  • To foster effective, transparent, and ethical progress in healthcare MI.

Main Methods:

  • A workshop co-hosted by NIH, NCATS, NCI, and NIBIB on July 12, 2019.
  • Discussions involved researchers, clinicians, patient advocates, industry, academia, and federal agencies.
  • Key topics included data quality, EHR access, system transparency, explainability, and bias.

Main Results:

  • Identified critical issues in applying MI to healthcare.
  • Highlighted the need for improved data quality, accessibility, and EHR integration.
  • Emphasized the importance of transparency, explainability, and mitigating bias in MI systems.

Conclusions:

  • Addressing identified challenges is essential for accelerating MI progress in healthcare.
  • Proposed avenues and solutions aim to guide the effective, transparent, and ethical deployment of MI.
  • Collaboration and focused improvements can unlock MI's full potential in the health ecosystem.