Evidence map›Paper›PMID 37065355›Full record

ReviewCureus2023

Imaging in Healthcare: A Glance at the Present and a Glimpse Into the Future.

Eman Nabrawi, Abdullah T Alanazi

Abstract readReview
In one paragraph

Review in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. The State of High-Resolution Imaging of the Human Inner Ear: A Look Into the Black Box.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  2. Article
  3. Scalable, reproducible, and cost-effective processing of large-scale medical imaging datasets.Proceedings of SPIE--the International Society for Optical Engineering · 2025
    Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Teleradiology: Geography is now History!Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2024
    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

2 authors.

Eman NabrawiDepartment of Health Informatics, King Saud bin Abdulaziz University for Health Sciences (KSAU-HS), Riyadh, SAU.
Abdullah T AlanaziDepartment of Health Informatics, College of Public Health and Health Informatics, King Saud bin Abdul-Aziz University for Health Science (KSAU-HS), Riyadh, SAU.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The utilization of artificial intelligence (AI) applications in medical imaging relies heavily on imaging informatics. That is a one-of-a-kind professional who works at the crossroads of clinical radiography, data science, and information technology. Imaging informaticians are becoming crucial players in expanding, assessing, and implementing AI in the medical setting. Teleradiology will continue to be a cost-effective healthcare facility that expands. Vendor neutral archive (VNA) isolates image presentation and storing systems, permitting platforms to develop quickly, and is a repository for organization-wide healthcare image data. Efforts are made to incorporate and integrate diagnostic facilities such as radiography and pathology to fulfill the needs and demands of targeted therapy. Developments in computer-aided medical object identification may alter the environment of patient services. Finally, interpreting and processing distinct complex healthcare data will create a data-rich context where evidence-based care and performance development may be driven.

Indexed as

image informaticsimage in healthcareimage miningpacsvendor neutral archive (vna)

Identifiers

PMID37065355
PMCPMC10098436

What OpenQuestion holds

Textmetadata
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.