Evidence map›Paper›PMID 37829937›Full record

ArticleCureus2023

Healthcare in Vietnam: Harnessing Artificial Intelligence and Robotics to Improve Patient Care Outcomes.

Tu N Doan Thu, Quan K Nguyen, Andrew W Taylor-Robinson

Abstract readEditorial
In one paragraph

Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
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.

Tu N Doan ThuBusiness and Management, College of Business and Management, VinUniversity, Hanoi, VNM.
Quan K NguyenEpidemiology and Public Health, College of Health Sciences, VinUniversity, Hanoi, VNM.
Andrew W Taylor-RobinsonEpidemiology and Public Health, College of Health Sciences, VinUniversity, Hanoi, VNM.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Healthcare in Vietnam is increasingly utilizing artificial intelligence (AI) and robotics to enhance patient care outcomes. The Vietnamese healthcare sector recognizes the potential of AI and is actively exploring its applications in research and clinical practice. AI technologies, such as text mining and machine learning, can be employed to analyze medical data and improve decision-making processes. Robotics, on the other hand, can support various healthcare tasks, including elderly care, rehabilitation, and surgical interventions. Robotic surgery, specifically, is an innovative form of minimally invasive surgery that aims to improve surgical outcomes and enhance the patient experience. The implementation of AI in emergency and trauma settings is still in its early stages, but there is a growing interest in and recognition of its potential benefits. However, there are challenges that need to be addressed, such as the need for appropriate research and training programs to support the adoption and integration of AI in healthcare. Despite these challenges, healthcare professionals in Vietnam are optimistic about the potential of AI to improve acute care surgery and are open to embracing new digital technologies. The use of AI and robotics in healthcare aligns with the broader goal of improving healthcare systems in low- and middle-income countries, including Vietnam, through technological advancements. Overall, AI can play an important role in assisting prognosis and predictive analysis by integrating vast amounts of data. Moreover, the integration of AI and robotics in healthcare in Vietnam has the potential to enhance patient care outcomes, improve decision-making processes, and support healthcare professionals in their practice.

Indexed as

ai & robotics in healthcareartificial intelligencedigital technologyhealthcareroboticssurgeryvietnam

Identifiers

PMID37829937
PMCPMC10565519

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.