Evidence map›Paper›PMID 35327938›Full record

ArticleEntropy (Basel, Switzerland)2022

Machine Learning Models and Statistical Complexity to Analyze the Effects of Posture on Cerebral Hemodynamics.

Max Chacón, Hector Rojas-Pescio, Sergio Peñaloza, Jean Landerretche

Open access · goldAbstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2022. 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
0.6field-weighted citation impact, top 32% of its field
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, 5 citations in OpenAlex.

  1. Review
  2. Time-domain methods for quantifying dynamic cerebral blood flow autoregulation: Review and recommendations. A white paper from the Cerebrovascular Research Network (CARNet).Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2024
    Review
  3. 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 at 1 institution in 1 country.

Max ChacónDepartamento de Ingeniería Informática, Universidad de Santiago de Chile, Av. Víctor Jara N° 2659, Estación Central, Santiago 9190864, Chile.ORCID 0000-0002-5082-0395
Hector Rojas-PescioDepartamento de Ingeniería Informática, Universidad de Santiago de Chile, Av. Víctor Jara N° 2659, Estación Central, Santiago 9190864, Chile.ORCID 0000-0002-9543-3516
Sergio PeñalozaDepartamento de Ingeniería Informática, Universidad de Santiago de Chile, Av. Víctor Jara N° 2659, Estación Central, Santiago 9190864, Chile.ORCID 0000-0001-9413-5309
Jean LanderretcheUnidad de Neurología, Escuela de Medicina, Universidad de Santiago de Chile, Av. Alameda N° 3336, Estación Central, Santiago 9170022, Chile.
Universidad de Santiago de Chile · CL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The mechanism of cerebral blood flow autoregulation can be of great importance in diagnosing and controlling a diversity of cerebrovascular pathologies such as vascular dementia, brain injury, and neurodegenerative diseases. To assess it, there are several methods that use changing postures, such as sit-stand or squat-stand maneuvers. However, the evaluation of the dynamic cerebral blood flow autoregulation (dCA) in these postures has not been adequately studied using more complex models, such as non-linear ones. Moreover, dCA can be considered part of a more complex mechanism called cerebral hemodynamics, where others (CO

Indexed as

cerebral hemodynamicsmachine learning modelspostural effectsstatistic complexity

Identifiers

PMID35327938
PMCPMC8947420
OpenAlexW4220706021

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.