Evidence map›Paper›PMID 39262497›Full record

ArticleComputational intelligence and neuroscience2023

Biomedical Text Classification Using Augmented Word Representation Based on Distributional and Relational Contexts.

Md Aslam Parwez, Mohd Fazil, Muhammad Arif, Md Tabrez Nafis, Md Rabiul Auwul

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2023. 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

5 authors.

Md Aslam ParwezDepartment of Computer Science & Engineering, Jamia Hamdard, New Delhi, India.
Mohd FazilUniversity of Limerick, Limerick, Ireland.
Muhammad ArifDepartment of Computer Science, Superior University Lahore, Lahore 54000, Pakistan.ORCID https://orcid.org/0000-0002-7449-2701
Md Tabrez NafisDepartment of Computer Science & Engineering, Jamia Hamdard, New Delhi, India.ORCID https://orcid.org/0000-0002-3395-8448
Md Rabiul AuwulDepartment of Statistics, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur 1706, Bangladesh.ORCID https://orcid.org/0000-0003-2505-5422

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to the increasing use of information technologies by biomedical experts, researchers, public health agencies, and healthcare professionals, a large number of scientific literatures, clinical notes, and other structured and unstructured text resources are rapidly increasing and being stored in various data sources like PubMed. These massive text resources can be leveraged to extract valuable knowledge and insights using machine learning techniques. Recent advancement in neural network-based classification models has gained popularity which takes numeric vectors (

Identifiers

PMID39262497
PMCPMC11390191

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.