Evidence map›Paper›PMID 39162839›Full record

ArticleJournal of clinical monitoring and computing2024

Imitating the respiratory activity of the brain stem by using artificial neural networks: exploratory study on an animal model of lactic acidosis and proof of concept.

Gaetano Perchiazzi, Rafael Kawati, Mariangela Pellegrini, Jasmine Liangpansakul, Roberto Colella, Paolo Bollella, Pramod Rangaiah, Annamaria Cannone, Deepthi Hulithala Venkataramana, Mauricio Perez and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of clinical monitoring and computing, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

14 authors.

Gaetano PerchiazziThe Hedenstierna Laboratory, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden. gaetano.perchiazzi@uu.se.ORCID 0000-0001-6834-6399
Rafael KawatiDepartment of Anesthesia, Operation and Intensive Care, Uppsala University Hospital, Uppsala, Sweden.
Mariangela PellegriniThe Hedenstierna Laboratory, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Jasmine LiangpansakulThe Hedenstierna Laboratory, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Roberto ColellaMinistry of Education and Merit, Rome, Italy.
Paolo BollellaDepartment of Chemistry, University of Bari Aldo Moro, Bari, Italy.
Pramod RangaiahDepartment of Electrical Engineering, Solid-State Electronics, Uppsala University, Uppsala, Sweden.
Annamaria CannoneDepartment of Anaesthesia and Intensive Care, "Madonna delle Grazie" Hospital, Matera, Italy.
Deepthi Hulithala VenkataramanaDepartment of Information Technology, Uppsala University, Uppsala, Sweden.
Mauricio PerezDepartment of Electrical Engineering, Solid-State Electronics, Uppsala University, Uppsala, Sweden.
Sebastiano StramagliaDipartimento Interateneo di Fisica, Università degli Studi di Bari, Rome, Italy.
Luisa TorsiDepartment of Chemistry, University of Bari Aldo Moro, Bari, Italy.
Roberto BellottiDipartimento Interateneo di Fisica, Università degli Studi di Bari, Rome, Italy.
Robin AugustineDepartment of Electrical Engineering, Solid-State Electronics, Uppsala University, Uppsala, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial neural networks (ANNs) are versatile tools capable of learning without prior knowledge. This study aims to evaluate whether ANN can calculate minute volume during spontaneous breathing after being trained using data from an animal model of metabolic acidosis. Data was collected from ten anesthetized, spontaneously breathing pigs divided randomly into two groups, one without dead space and the other with dead space at the beginning of the experiment. Each group underwent two equal sequences of pH lowering with pre-defined targets by continuous infusion of lactic acid. The inputs to ANNs were pH, ΔPaCO

Indexed as

Acidosis, LacticBrain StemDisease Models, AnimalLactic AcidNeural Networks, ComputerRespirationAlgorithmsAnimalsBlood Gas AnalysisBody TemperatureCarbon DioxideHydrogen-Ion ConcentrationLinear ModelsProof of Concept StudySwineCarbon DioxideLactic AcidArtificial neural networksClosed loopLactic acidosisMechanical ventilationTranslational model

Identifiers

PMID39162839
PMCPMC11604730

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.