Evidence map›Paper›PMID 34113262›Full record

ArticleFrontiers in physiology2021

BayCANN: Streamlining Bayesian Calibration With Artificial Neural Network Metamodeling.

Hawre Jalal, Thomas A Trikalinos, Fernando Alarid-Escudero

Abstract read
In one paragraph

Article in Frontiers in physiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. A Metamodel-Based General-Purpose Autocalibration Tool for Simulation Models.Medical decision making : an international journal of the Society for Medical Decision Making · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Meta-Modeling as a Variance-Reduction Technique for Stochastic Model-Based Cost-Effectiveness Analyses.Medical decision making : an international journal of the Society for Medical Decision Making · 2025
    Article
  6. A Scoping Review on Calibration Methods for Cancer Simulation Models.Medical decision making : an international journal of the Society for Medical Decision Making · 2025
    Article
  7. Microsimulation Estimates of Decision Uncertainty and Value of Information Are Biased but Consistent.Medical decision making : an international journal of the Society for Medical Decision Making · 2025
    Article
  8. Emulator-Based Bayesian Calibration of the CISNET Colorectal Cancer Models.Medical decision making : an international journal of the Society for Medical Decision Making · 2024
    Article
  9. Modeling Thyroid Cancer Epidemiology in the United States Using Papillary Thyroid Carcinoma Microsimulation Model.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2024
    Article
  10. Emulator-based Bayesian calibration of the CISNET colorectal cancer models.medRxiv : the preprint server for health sciences · 2024
    Article
  11. Calibration and Validation of the Colorectal Cancer and Adenoma Incidence and Mortality (CRC-AIM) Microsimulation Model Using Deep Neural Networks.Medical decision making : an international journal of the Society for Medical Decision Making · 2023
    Article
  12. Article
  13. 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

3 authors.

Hawre JalalDepartment of Health Policy and Management, University of Pittsburgh, Graduate School of Public Health, Pittsburgh, PA, United States.
Thomas A TrikalinosDepartments of Health Services, Policy & Practice and Biostatistics, Brown University, Providence, RI, United States.
Fernando Alarid-EscuderoDivision of Public Administration, Center for Research and Teaching in Economics (CIDE), Aguascalientes, Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

artificial neural networksBayesian calibrationemulatorsmachine learningmechanistic modelsmetamodelssurrogate models

Identifiers

PMID34113262
PMCPMC8185956

What OpenQuestion 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 OpenQuestion graph.