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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

38
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
38
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

23
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
23

You might also read

Related Articles

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

Sort by
Same author

Establishment and characterization of an ovarian cell line from red seabream (Pagrus major) and its application in fish toxicology.

In vitro cellular & developmental biology. Animal·2026
Same author

Epithelial FOXP3 Orchestrates O-Glycosylated IL6 Secretion to Drive Pancreatic Fibrocarcinogenesis.

Gastroenterology·2026
Same author

PIVOTS: Aligning unseen structures using preoperative to intraoperative volume-to-surface registration for liver navigation.

Medical image analysis·2026
Same author

Optimizing the integrated green-gray-blue system helps improve urban flood resilience under a non-stationary climate.

Journal of environmental management·2026
Same author

Biomimetic nanomodulator reprograms glycolysis-driven immunosuppressive microenvironment to potentiate photothermal immunotherapy in cold tumors.

Materials today. Bio·2026
Same author

Mitophagy‑Competent Cancer‑Associated Fibroblasts Fuel Chemoresistance by Rewiring Pyrimidine Metabolism in Pancreatic Cancer.

Cancer research·2026
Same journal

Multimodal Contrastive Spatiotemporal Self-Organizing Neural Networks for In-Home Activity Learning of Mild Cognitive Impairment.

IEEE journal of biomedical and health informatics·2026
Same journal

Integrating Multi-View Residue Graph and Protein Language Model for Cell-Penetrating Peptide Prediction via Global-Local Graph Aggregation and Cross-Attentive Fusion.

IEEE journal of biomedical and health informatics·2026
Same journal

An Ultra-Lightweight Cross-scale Attention Mamba Network for Accurate Skin Lesion Segmentation.

IEEE journal of biomedical and health informatics·2026
Same journal

Explanation-Guided Reconstruction of Missing Clinical Features for Survival Prediction in Pancreatic Cancer.

IEEE journal of biomedical and health informatics·2026
Same journal

stDGCN: A dual-augmentation graph convolutional network for identifying spatial domains with attention mechanism.

IEEE journal of biomedical and health informatics·2026
Same journal

Patient-specific Biomechanical Investigation of Percutaneous Pulmonary Valves: Towards the Integration of Routinely Acquired Clinical Data and Fluid-structure Interaction Simulations.

IEEE journal of biomedical and health informatics·2026
See all related articles

Related Experiment Video

Updated: May 24, 2025

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

475

The Large Language Models on Biomedical Data Analysis: A Survey.

Wei Lan, Zhentao Tang, Mingyang Liu

    IEEE Journal of Biomedical and Health Informatics
    |March 3, 2025
    PubMed
    Summary
    This summary is machine-generated.

    This review summarizes Large Language Model (LLM) applications in biomedical data analysis, covering techniques, datasets, and challenges. It aims to equip researchers with knowledge for applying LLM in diverse biomedical fields.

    More Related Videos

    Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
    07:15

    Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

    Published on: August 16, 2020

    6.6K
    A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
    07:35

    A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

    Published on: October 13, 2023

    1.5K

    Related Experiment Videos

    Last Updated: May 24, 2025

    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

    475
    Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
    07:15

    Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

    Published on: August 16, 2020

    6.6K
    A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
    07:35

    A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

    Published on: October 13, 2023

    1.5K

    Area of Science:

    • Biomedical data analysis
    • Artificial Intelligence
    • Bioinformatics

    Background:

    • Large Language Models (LLMs) are rapidly advancing and crucial for biomedical research.
    • Biomedical researchers require more knowledge on LLM applications.
    • A comprehensive summary of LLM in biomedicine is needed.

    Purpose of the Study:

    • To review and summarize the latest research on Large Language Model applications in biomedical data analysis.
    • To provide an overview of LLM techniques, datasets, and frameworks relevant to biomedicine.
    • To highlight LLM applications across various biomedical domains and discuss associated challenges.

    Main Methods:

    • Literature review of recent research on LLMs in biomedicine.
    • Outline of LLM techniques and relevant biomedical datasets and frameworks.
    • Detailed analysis of LLM applications in genomics, proteomics, transcriptomics, radiomics, single-cell analysis, medical texts, and drug discovery.

    Main Results:

    • LLMs are being applied across diverse biomedical fields including genomics, proteomics, and drug discovery.
    • The review covers essential LLM techniques and data analysis frameworks.
    • Key challenges and future directions for LLMs in biomedical data analysis are identified.

    Conclusions:

    • This review provides a comprehensive overview of LLM applications in biomedical data analysis.
    • It serves as a guide for researchers seeking to understand and utilize LLM technology.
    • The findings aim to facilitate the integration of LLMs into biomedical research workflows.