Evidence map›Paper›PMID 39317229›Full record

ArticleJournal of radiological protection : official journal of the Society for Radiological Protection2024

Machine learning-enhanced stochastic uncertainty and sensitivity analysis of the ICRP human respiratory tract model for an inhaled radionuclide.

Emmanuel Matey Mate-Kole, Sara C Howard, Ashley P Golden, Shaheen Azim Dewji

Abstract read
In one paragraph

Article in Journal of radiological protection : official journal of the Society for Radiological Protection, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Reconstructing strontium-90 intake in beagles using neural networks: a data-driven assessment of historical inhalation records.Journal of radiological protection : official journal of the Society for Radiological Protection · 2025
    Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Emmanuel Matey Mate-KoleNuclear and Radiological Engineering and Medical Physics Programs, Georgia Institute of Technology, Atlanta, GA, United States of America.ORCID 0000-0003-4311-6559
Sara C HowardEpidemiology and Exposure Science, Oak Ridge Associated Universities, Oak Ridge, TN, United States of America.ORCID 0000-0002-9290-4319
Ashley P GoldenEpidemiology and Exposure Science, Oak Ridge Associated Universities, Oak Ridge, TN, United States of America.ORCID 0000-0002-9430-7702
Shaheen Azim DewjiNuclear and Radiological Engineering and Medical Physics Programs, Georgia Institute of Technology, Atlanta, GA, United States of America.ORCID 0000-0002-3699-5877

Funding

Project 4: Post-Exposure Biomarkers and Remediation of Radionuclide ContaminantsP01AI165380 · NIAID · NORTHWESTERN UNIVERSITY AT CHICAGO · PI WESLEY E BOLCH · 2022 to 2026
$12.9M
Department of Defense W81XWH-21-1-0984NIAID NIH HHS P01 AI165380
6 · The paper itself

Abstract

The International Commission on Radiological Protection (ICRP) has developed the reference Human Respiratory Tract Model (HRTM), detailed in ICRP Publications 66 and 130, to estimate the deposition and clearance of inhaled radionuclides. These models utilize reference anatomical and physiological parameters for particle deposition (PD). Biokinetic models further estimate retention and excretion of internalized particulates, aiding the derivation of inhalation dose coefficients (DC). This study aimed to assess variability in deterministic

Indexed as

Machine LearningRespiratory SystemStochastic ProcessesHumansInhalation ExposureModels, BiologicalOccupational ExposureRadiation DosageRadiation ProtectionRadioisotopesUncertaintyRadioisotopesbiokinetic modelsICRP HRTMmachine learningstochastic expansionuncertainty and sensitivity analysis

Identifiers

PMID39317229
PMCPMC11481712

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.