Evidence map›Paper›PMID 36780238›Full record

ArticleRecent trends in image processing and pattern recognition : 5th International Conference, RTIP2R 2022, Kingsville, TX, USA, December 01-02, 2022, revised selected papers. International Conference on Recent Trends in Image Processing and...2023

Data Characterization for Reliable AI in Medicine.

Sivaramakrishnan Rajaraman, Ghada Zamzmi, Feng Yang, Zhiyun Xue, Sameer K Antani

Abstract read
In one paragraph

Article in Recent trends in image processing and pattern recognition : 5th International Conference, RTIP2R 2022, Kingsville, TX, USA, December 01-02, 2022, revised selected papers. International Conference on Recent Trends in Image Processing and..., 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Weakly Supervised Learning of Oral Cavity Images for Separating Precancer from Cancer.IEEE International Conference on Omni-layer Intelligent Systems : COINS. IEEE International Conference on Omni-layer Intelligent Systems · 2026
    Article
  2. Oral Cancer Detection By Using Tabular Data Synthesis and Classification.Proceedings ... ICDM workshops. IEEE International Conference on Data Mining · 2025
    Article
  3. Article
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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.

Sivaramakrishnan RajaramanComputational Health Research Branch, National Library of Medicine, National Institutes of Health, Bethesda MD 20894, USA.ORCID 0000-0003-0871-8634
Ghada ZamzmiComputational Health Research Branch, National Library of Medicine, National Institutes of Health, Bethesda MD 20894, USA.ORCID 0000-0003-4723-5539
Feng YangComputational Health Research Branch, National Library of Medicine, National Institutes of Health, Bethesda MD 20894, USA.ORCID 0000-0002-8334-7450
Zhiyun XueComputational Health Research Branch, National Library of Medicine, National Institutes of Health, Bethesda MD 20894, USA.ORCID 0000-0003-0644-385X
Sameer K AntaniComputational Health Research Branch, National Library of Medicine, National Institutes of Health, Bethesda MD 20894, USA.ORCID 0000-0002-0040-1387

Funding

Machine learning and artificial intelligence research for clinical medical image processingZIALM010018 · NLM · NATIONAL LIBRARY OF MEDICINE · PI ANTANI, SAMEER · 2021 to 2025
$9.0M
Intramural NIH HHS Z99 LM999999Intramural NIH HHS ZIA LM010018
6 · The paper itself

Abstract

Research in Artificial Intelligence (AI)-based medical computer vision algorithms bear promises to improve disease screening, diagnosis, and subsequently patient care. However, these algorithms are highly impacted by the characteristics of the underlying data. In this work, we discuss various data characteristics, namely

Indexed as

artificial intelligenceData characteristicsdata-driven designdeep learninggeneralizabilitymachine learningmedical imagingreliabilityrobustness

Identifiers

PMID36780238
PMCPMC9912175

What OpenQuestion holds

Textmetadata
LicenceTDM
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.