Evidence map›Paper›PMID 31304332›Full record

ArticleNPJ digital medicine2018

Health intelligence: how artificial intelligence transforms population and personalized health.

Arash Shaban-Nejad, Martin Michalowski, David L Buckeridge

Registry-linked trialAbstract readEditorial
In one paragraph

Article in NPJ digital medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05214625 (Questionnaire Study Concerning Artificial Intelligence and Its Application in), which is not on this map. Cited by 77 papers.

0numbers the graph read from it
0cells of the map it votes in
77citing 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.

NCT05214625 completednot on this mapstarted 2020, after this paper: background citation

Questionnaire Study Concerning Artificial Intelligence and Its Application in (Gastrointestinal) Healthcare - Patients' and Physicians' Perspectives

TypeobservationalSponsorMaastricht University Medical CenterRan2020 to 2021Enrolled457ConditionsGastro-Intestinal DisordersArmsQuestionnaire
3 · Its place in the literature

Who cites it

77 citing papers in PubMed.

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  19. Mental Health Applications of Generative AI and Large Language Modeling in the United States.International journal of environmental research and public health · 2024
    Article
  20. Review

17 more citing papers are in PubMed but not listed here.

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

3 authors.

Arash Shaban-Nejad1Department of Pediatrics, University of Tennessee Health Science Center - Oak Ridge National Laboratory (UTHSC-ORNL) Center for Biomedical Informatics, Memphis, TN USA.ORCID 0000-0003-2047-4759
Martin Michalowski2School of Nursing, University of Minnesota, Minneapolis, MN USA.ORCID 0000-0003-2060-5878
David L BuckeridgeDepartment of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advances in computational and data sciences for data management, integration, mining, classification, filtering, visualization along with engineering innovations in medical devices have prompted demands for more comprehensive and coherent strategies to address the most fundamental questions in health care and medicine. Theory, methods, and models from artificial intelligence (AI) are changing the health care landscape in clinical and community settings and have already shown promising results in multiple applications in healthcare including, integrated health information systems, patient education, geocoding health data, social media analytics, epidemic and syndromic surveillance, predictive modeling and decision support, mobile health, and medical imaging (e.g. radiology and retinal image analyses). Health intelligence uses tools and methods from artificial intelligence and data science to provide better insights, reduce waste and wait time, and increase speed, service efficiencies, level of accuracy, and productivity in health care and medicine.

Indexed as

Population screeningResearch management

Identifiers

PMID31304332
PMCPMC6550150

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.