Evidence map›Paper›PMID 35283490›Full record

ArticleBiomedical engineering2022

Some Methods for Substantiating Diagnostic Decisions Made Using Machine Learning Algorithms.

A G Losev, I E Popov, A Yu Petrenko, A G Gudkov, S G Vesnin, S V Chizhikov

Abstract read
In one paragraph

Article in Biomedical engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

A G LosevVolgograd State University, Volgograd, Russia.
I E PopovVolgograd State University, Volgograd, Russia.
A Yu PetrenkoVolgograd State University, Volgograd, Russia.
A G GudkovBauman Moscow State Technical University, Moscow, Russia.
S G VesninRES Company, Moscow, Russia.
S V ChizhikovBauman Moscow State Technical University, Moscow, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Various classification algorithms used in the diagnosis of breast cancer based on microwave radiometry data are considered. In particular, their principles of operation and the possibility of substantiating diagnoses using numerical data are discussed. A substantiation algorithm based on decision trees and a naive Bayesian classifier is presented. Examples of substantiation are given for breast cancer.

Identifiers

PMID35283490
PMCPMC8898747

What OpenQuestion holds

Textmetadata
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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.