Evidence map›Paper›PMID 39684952›Full record

ReviewHealthcare (Basel, Switzerland)2024

The Frontiers of Smart Healthcare Systems.

Nan Lin, Rudy Paul, Santiago Guerra, Yan Liu, James Doulgeris, Min Shi, Maohua Lin, Erik D Engeberg, Javad Hashemi, Frank D Vrionis

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Healthcare (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Nan LinDepartment of Gastroenterology, The Affiliated Hospital of Putian University, Putian 351100, China.
Rudy PaulDepartment of Ocean & Mechanical Engineering, Florida Atlantic University, Boca Raton, FL 33431, USA.ORCID 0000-0002-0124-992X
Santiago GuerraDepartment of Ocean & Mechanical Engineering, Florida Atlantic University, Boca Raton, FL 33431, USA.
Yan LiuDepartment of Gastroenterology, The Affiliated Hospital of Putian University, Putian 351100, China.
James DoulgerisDepartment of Biomedical Engineering, Florida Atlantic University, Boca Raton, FL 33431, USA.
Min ShiHarvard Ophthalmology AI Lab, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, MA 02115, USA.
Maohua LinDepartment of Biomedical Engineering, Florida Atlantic University, Boca Raton, FL 33431, USA.ORCID 0000-0002-9460-2111
Erik D EngebergDepartment of Ocean & Mechanical Engineering, Florida Atlantic University, Boca Raton, FL 33431, USA.ORCID 0000-0002-2340-1881
Javad HashemiDepartment of Biomedical Engineering, Florida Atlantic University, Boca Raton, FL 33431, USA.
Frank D VrionisDepartment of Neurosurgery, Marcus Neuroscience Institute, Boca Raton Regional Hospital, Boca Raton, FL 33486, USA.ORCID 0009-0006-0259-8618

Funding

National Science Foundation 2205205
6 · The paper itself

Abstract

Artificial Intelligence (AI) is poised to revolutionize numerous aspects of human life, with healthcare among the most critical fields set to benefit from this transformation. Medicine remains one of the most challenging, expensive, and impactful sectors, with challenges such as information retrieval, data organization, diagnostic accuracy, and cost reduction. AI is uniquely suited to address these challenges, ultimately improving the quality of life and reducing healthcare costs for patients worldwide. Despite its potential, the adoption of AI in healthcare has been slower compared to other industries, highlighting the need to understand the specific obstacles hindering its progress. This review identifies the current shortcomings of AI in healthcare and explores its possibilities, realities, and frontiers to provide a roadmap for future advancements.

Indexed as

Artificial Intelligence (AI)healthcaremedical imagingsmart healthcare systemssurgery

Identifiers

PMID39684952
PMCPMC11641075

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.