Related Experiment Video

Updated: Aug 26, 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

526

Extending the Nested Model for User-Centric XAI: A Design Study on GNN-based Drug Repurposing.

Qianwen Wang, Kexin Huang, Payal Chandak

    IEEE Transactions on Visualization and Computer Graphics
    |October 12, 2022
    PubMed
    Summary

    Visualizing AI explanations is key for usability. This study designs usable visual explanations for graph neural network (GNN) predictions in drug repurposing, creating the DrugExplorer tool.

    More Related Videos

    Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System05:10

    Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

    Published on: December 11, 2016

    9.7K
    Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness03:14

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

    Published on: December 6, 2024

    671

    Related Concept Videos

    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...
    991
    Model Approaches for Pharmacokinetic Data: Compartment Models01:14

    Model Approaches for Pharmacokinetic Data: Compartment Models

    Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
    Two primary types of compartment models are recognized: mammillary and catenary. The more...
    179
    Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

    Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

    Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
    The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
    119
    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...
    144
    Model Approaches for Pharmacokinetic Data: Physiological Models01:15

    Model Approaches for Pharmacokinetic Data: Physiological Models

    Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
    96
    Structure-Activity Relationships and Drug Design01:28

    Structure-Activity Relationships and Drug Design

    Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
    SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence...
    970