Evidence map›Paper›PMID 36144434›Full record

ReviewMicroorganisms2022

Dietary Efficacy Evaluation by Applying a Prediction Model Using Clinical Fecal Microbiome Data of Colorectal Disease to a Controlled Animal Model from an Obesity Perspective.

Hochan Seo, Cheol-O Kwon, Joo-Hyun Park, Chil-Sung Kang, Tae-Seop Shin, Eun-Young Yang, Jin Woo Jung, Byoung-Seok Moon, Yoon-Keun Kim

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Microorganisms, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 38% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
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

9 authors at 1 institution in 1 country.

Hochan SeoR&D Center of MD Healthcare Inc., 9, World Cup Buk-ro 56-gil, Mapo-gu, Seoul 03923, Korea.
Cheol-O KwonR&D Center of MD Healthcare Inc., 9, World Cup Buk-ro 56-gil, Mapo-gu, Seoul 03923, Korea.
Joo-Hyun ParkR&D Center of MD Healthcare Inc., 9, World Cup Buk-ro 56-gil, Mapo-gu, Seoul 03923, Korea.
Chil-Sung KangR&D Center of MD Healthcare Inc., 9, World Cup Buk-ro 56-gil, Mapo-gu, Seoul 03923, Korea.ORCID 0000-0002-6357-2677
Tae-Seop ShinR&D Center of MD Healthcare Inc., 9, World Cup Buk-ro 56-gil, Mapo-gu, Seoul 03923, Korea.ORCID 0000-0002-8165-0595
Eun-Young YangR&D Center, HK inno.N Corporation, 811, Deokpyeong-ro, Majang-myeon, Icheon-si, Gyeonggi-do 17389, Korea.
Jin Woo JungR&D Center, HK inno.N Corporation, 811, Deokpyeong-ro, Majang-myeon, Icheon-si, Gyeonggi-do 17389, Korea.
Byoung-Seok MoonKolmar Korea R&D Complex, HK Kolmar Holdings, 61, Heolleung-ro 8-gil, Seocho-gu, Seoul 06800, Korea.
Yoon-Keun KimR&D Center of MD Healthcare Inc., 9, World Cup Buk-ro 56-gil, Mapo-gu, Seoul 03923, Korea.
Kolmar Korea (South Korea) · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Obesity associated with a Western diet such as a high-fat diet (HFD) is a known risk factor for inflammatory bowel disease (IBD) and colorectal cancer (CRC). In this study, we aimed to develop fecal microbiome data-based deep learning algorithms for the risk assessment of colorectal diseases. The effects of a HFD and a candidate food (

Indexed as

16S amplicon sequencingcolorectal cancergradient boosting machineinflammatory bowel diseasemicrobiomeNypa fruticansobesity

Identifiers

PMID36144434
PMCPMC9505706
OpenAlexW4295778989

What OpenQuestion holds

Textmetadata
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.