Evidence map›Paper›PMID 37574841›Full record

ArticleTechnology in cancer research & treatment

Novel Applications of Artificial Intelligence in Cancer Research.

Masayuki Tsuneki, Yudong Zhang

Abstract readEditorial
In one paragraph

Article in Technology in cancer research & treatment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Masayuki TsunekiMedical Research (Medmain Research), Medmain Inc, Fukuoka, Japan.ORCID 0000-0003-3409-5485
Yudong ZhangSchool of Computing and Mathematical Sciences, University of Leicester, Leicester, UK.ORCID 0000-0002-4870-1493

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cutting-edge developments in machine learning and deep learning are improving all aspects of cancer research and treatment. Nowadays, the applications of artificial intelligence, machine learning, and deep learning to clinical aspects of cancer research have received more attention from scholars, with particular emphasis on diagnosis, prognosis, detection, and treatment.

Indexed as

Artificial IntelligenceNeoplasmsHumansMachine LearningPrognosisartificial intelligencedeep learningdiagnosismachine learningmedical image analysistreatment

Identifiers

PMID37574841
PMCPMC10426296

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.