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

Reasoning01:30

Reasoning

566
Reasoning is the action of thinking about something in a logical, sensible way. It is integral to problem-solving, decision-making, and critical thinking. Reasoning can be inductive or deductive. Reasoning involves transforming information into conclusions, which is essential for problem-solving, decision-making, and critical thinking.
Inductive reasoning involves deriving generalizations from specific observations. This type of reasoning helps form beliefs about the world. For example,...
566
Patient-centered Care01:13

Patient-centered Care

3.1K
Patient-centered care involves delivering care beyond inpatient hospitalization. Reflective practice can enhance a patient-centered approach. Reflective practice is a process of reasoning that considers all aspects of the present situation, including practicalities, learning from personal practice, and consideration of patient needs. Patients appreciate care decisions made while considering their input. Involving the patient in their care provides the patient with a sense of contribution rather...
3.1K
Critical Thinking II01:25

Critical Thinking II

5.3K
Critical thinking is a cognitive process with several attributes. The attributes of critical thinking include the following:
5.3K
Critical Thinking I01:24

Critical Thinking I

5.3K
Critical thinking helps decision-making and allows nurses to recognize barriers to success and find solutions to possible issues. It helps to brainstorm and implement ideas to achieve goals. Critical thinking helps acknowledge and state workflow inefficiencies while improving management techniques. Nurses understand the value of critical thinking and look for fellow nurses with critical thinking skills to upgrade their professional standards. Critical thinking can advance a nurse's career...
5.3K
Inductive Reasoning00:59

Inductive Reasoning

59.0K
Inductive reasoning is a form of logical thinking that uses related observations to arrive at a general conclusion. It is uncertain and operates in degrees to which the conclusions are credible. As such, inductive arguments can be weak or strong, rather than valid or invalid, and conclusions can be used to formulate testable, falsifiable hypotheses.
Inductive reasoning is common in descriptive science. A life scientist makes observations and records them. This data can be qualitative or...
59.0K
Deductive Reasoning01:16

Deductive Reasoning

59.5K
Deductive reasoning, or deduction, is the type of logic used in hypothesis-based science. In deductive reasoning, the pattern of thinking moves in the opposite direction as compared to inductive reasoning, which means that it uses a general principle or law to predict specific results. From those general principles, a scientist can deduce and predict the specific results that would be valid as long as the general principles are valid.
For example, a researcher can deduce specific predictions...
59.5K

You might also read

Related Articles

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

Sort by
Same author

Evaluating the Potential of Reasoning Large Language Models to Perpetuate Racial and Gender Disease Stereotypes in Health Care.

Journal of medical Internet research·2026
Same author

Cross-Sectional Evaluation of Medical Disinformation Safeguards in Consumer-Facing Large Language Model Platforms.

JMIR infodemiology·2026
Same author

HSR26-204: Baseline EORTC QLQ-C30 "Clinically Important" Symptom Burden Predicts Survival and Toxicity in CLL/SLL Across Randomized Ibrutinib Trials.

Journal of the National Comprehensive Cancer Network : JNCCN·2026
Same author

Treatment-Specific Prediction Models in Multiple Myeloma: A Critical Review of Current Evidence and Future Directions.

European journal of haematology·2026
Same author

The carcinogenicity of e-cigarettes: a qualitative risk assessment.

Carcinogenesis·2026
Same author

HSR26-204: Baseline EORTC QLQ-C30 "Clinically Important" Symptom Burden Predicts Survival and Toxicity in CLL/SLL Across Randomized Ibrutinib Trials.

Journal of the National Comprehensive Cancer Network : JNCCN·2026

Related Experiment Video

Updated: May 2, 2026

The Adventures of Fundi Intervention Based on the Cognitive and Emotional Processing in Attention Deficit Hyperactive Disorder Patients
05:48

The Adventures of Fundi Intervention Based on the Cognitive and Emotional Processing in Attention Deficit Hyperactive Disorder Patients

Published on: June 12, 2020

5.4K

AI can reason like a physician-what comes next?

Ashley M Hopkins1, Erik Cornelisse1

  • 1College of Medicine and Public Health, Flinders Health and Medical Research Institute, Flinders University, Adelaide, Australia.

Science (New York, N.Y.)
|April 30, 2026
PubMed
Summary

Text-based artificial intelligence (AI) shows potential for physician-level thinking, but ensuring its safe use in clinical settings remains a significant hurdle.

Area of Science:

  • Artificial Intelligence in Medicine
  • Clinical Decision Support Systems
  • Medical Informatics

Background:

  • The integration of artificial intelligence (AI) into healthcare offers transformative potential.
  • Text-based AI models are increasingly demonstrating capabilities that mimic human reasoning.
  • Ensuring the safety and efficacy of AI in clinical practice is paramount.

Purpose of the Study:

  • To evaluate the cognitive capabilities of text-based AI in simulating physician-level thought processes.
  • To identify the key challenges and requirements for the safe clinical implementation of AI in healthcare.

Main Methods:

  • Review of current text-based AI models and their performance in simulated medical scenarios.
  • Analysis of existing frameworks for AI safety and regulatory considerations.

More Related Videos

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
Ole Isacson: Development of New Therapies for Parkinson's Disease
23:53

Ole Isacson: Development of New Therapies for Parkinson's Disease

Published on: April 29, 2007

7.5K

Related Experiment Videos

Last Updated: May 2, 2026

The Adventures of Fundi Intervention Based on the Cognitive and Emotional Processing in Attention Deficit Hyperactive Disorder Patients
05:48

The Adventures of Fundi Intervention Based on the Cognitive and Emotional Processing in Attention Deficit Hyperactive Disorder Patients

Published on: June 12, 2020

5.4K
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
Ole Isacson: Development of New Therapies for Parkinson's Disease
23:53

Ole Isacson: Development of New Therapies for Parkinson's Disease

Published on: April 29, 2007

7.5K
  • Expert consensus on critical factors for clinical deployment.

    • Main Results:

    • Text-based AI exhibits advanced reasoning abilities comparable to physicians in specific domains.
    • Significant challenges exist in validation, bias mitigation, and seamless integration into clinical workflows.
    • Robust regulatory oversight and continuous monitoring are essential for safe adoption.

    Conclusions:

    • Text-based AI possesses the potential to augment clinical decision-making.
    • The primary obstacle lies in developing and implementing rigorous safety protocols for clinical use.
    • Further research and development are needed to bridge the gap between AI capabilities and safe clinical application.