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Related Concept Videos

Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Mechanistic Models: Overview of Compartment Models01:21

Mechanistic Models: Overview of Compartment Models

Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
Introduction to Language of Pathophysiology ll01:17

Introduction to Language of Pathophysiology ll

This lesson explores key terms that describe how diseases progress, their outcomes, and their distribution in populations.Diagnostic tests identify diseases and monitor treatment. These include blood and urine tests, biopsies, imaging (X-ray, MRI), and detection of infectious agents.Remission is a reduction or disappearance of symptoms.Exacerbation refers to the worsening of symptoms, such as increased wheezing during an asthma attack.A precipitating factor triggers an acute episode, while a...
Leaky Scanning02:28

Leaky Scanning

During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA.  Marilyn Kozak discovered that the sequence RCCAUGG (where R stands for...
Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions01:15

Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions

PK–PD modeling has significantly influenced FDA regulatory decisions, particularly drug approval, dosage optimization, and labeling. These models integrate pharmacokinetics (PK) and pharmacodynamics (PD) to predict drug behavior and effects, aiding in optimizing dosing regimens and enhancing the probability of clinical trial success.One notable example is Nesiritide (Natrecor®), a recombinant human brain natriuretic peptide for treating acute decompensated congestive heart failure (CHF).
Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal assumptions,...

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Related Experiment Video

Updated: May 12, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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Published on: December 6, 2024

Clinical Plausibility in Large Language Model Robustness Testing for Medicine: A Scoping Review.

Yu Chang1,2, Ming-Hong Hsieh1,2, Po-Chung Ju1,2

  • 1Department of Psychiatry, Chung Shan Medical University Hospital, Taichung, 40106, Taiwan.

Journal of Medical Systems
|May 11, 2026
PubMed
Summary

Robustness testing for medical large language models (LLMs) often uses adversarial methods, not reflecting real clinical use. Future evaluations need clinically grounded, specialized testing for safe AI deployment.

Keywords:
Clinical decision support systemClinical plausibilityLarge language modelRed teamingRobustness testing

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

Published on: June 13, 2025

Area of Science:

  • Medical Artificial Intelligence
  • Natural Language Processing
  • Clinical Informatics

Background:

  • Large language models (LLMs) demonstrate potential in healthcare.
  • Rigorous validation is essential for clinical translation.
  • Current robustness testing methods may not align with authentic clinical scenarios.

Purpose of the Study:

  • To systematically map methodologies for LLM robustness testing in medicine.
  • To assess the clinical plausibility of these testing approaches.

Main Methods:

  • A scoping review following PRISMA-ScR guidelines.
  • Searched multiple databases (PubMed, Embase, Web of Science, etc.) from January 2023 to September 2025.
  • Two physician reviewers screened 5,331 articles, extracting data on testing methods, domains, and clinical plausibility.

Main Results:

  • 33 studies met criteria, mostly from 2025 (82%).
  • Common methods included misleading (49%) and adversarial prompts (39%).
  • Only 33% of studies used clinically plausible scenarios; expert involvement varied (58%).

Conclusions:

  • LLM robustness testing in medicine often prioritizes technical vulnerability over clinical realism.
  • Future frameworks require clinically grounded, longitudinal, and specialty-focused evaluations.
  • Enhanced testing is crucial for safe and effective LLM deployment in clinical practice.