Evidence map›Paper›PMID 38405441›Full record

ArticleACS omega2024

Comparative Study of Machine Learning-Based QSAR Modeling of Anti-inflammatory Compounds from Durian Extraction.

Amphawan Wiriyarattanakul, Wanting Xie, Borwornlak Toopradab, Sopon Wiriyarattanakul, Liyi Shi, Thanyada Rungrotmongkol, Phornphimon Maitarad

Abstract read
In one paragraph

Article in ACS omega, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
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  5. Article
  6. Predicting antioxidant activity of compounds based on chemical structure using machine learning methods.The Korean journal of physiology & pharmacology : official journal of the Korean Physiological Society and the Korean Society of Pharmacology · 2024
    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

7 authors.

Amphawan WiriyarattanakulProgram in Chemistry, Faculty of Science and Technology, Uttaradit Rajabhat University, Uttaradit 53000, Thailand.
Wanting XieResearch Center of Nano Science and Technology, College of Sciences, Shanghai University, Shanghai 200444, P. R. China.
Borwornlak ToopradabCenter of Excellence in Structural and Computational Biology, Department of Biochemistry, Chulalongkorn University, Bangkok 10330, Thailand.
Sopon WiriyarattanakulProgram in Computer Science, Faculty of Science and Technology, Uttaradit Rajabhat University, Uttaradit 53000, Thailand.
Liyi ShiResearch Center of Nano Science and Technology, College of Sciences, Shanghai University, Shanghai 200444, P. R. China.
Thanyada RungrotmongkolCenter of Excellence in Structural and Computational Biology, Department of Biochemistry, Chulalongkorn University, Bangkok 10330, Thailand.ORCID https://orcid.org/0000-0002-7402-3235
Phornphimon MaitaradResearch Center of Nano Science and Technology, College of Sciences, Shanghai University, Shanghai 200444, P. R. China.ORCID https://orcid.org/0000-0003-0035-0070

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative structure-activity relationship (QSAR) analysis, an

Identifiers

PMID38405441
PMCPMC10882656

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.