Evidence map›Paper›PMID 38801765›Full record

ArticleJournal of medical Internet research2024

Advances in the Application of AI Robots in Critical Care: Scoping Review.

Yun Li, Min Wang, Lu Wang, Yuan Cao, Yuyan Liu, Yan Zhao, Rui Yuan, Mengmeng Yang, Siqian Lu, Zhichao Sun and 3 more

Abstract readScoping Review
In one paragraph

Article in Journal of medical Internet research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–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

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  11. Application of Artificial Intelligence in Physical Rehabilitation of Patients Admitted to the Intensive Care Unit: A Scoping Review.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2025
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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

13 authors.

Yun Li *Medical School of Chinese PLA, Beijing, China.ORCID 0000-0001-9648-3948
Min Wang *Medical School of Chinese PLA, Beijing, China.ORCID 0000-0003-1865-9113
Lu Wang *Medical School of Chinese PLA, Beijing, China.ORCID 0000-0002-8912-5496
Yuan Cao *The Second Hospital, Hebei Medical University, Hebei, China.ORCID 0009-0009-5625-2307
Yuyan LiuMedical School of Chinese PLA, Beijing, China.ORCID 0009-0008-3068-9087
Yan ZhaoThe First Medical Centre, Chinese PLA General Hospital, Beijing, China.ORCID 0000-0003-4551-5027
Rui YuanMedical School of Chinese PLA, Beijing, China.ORCID 0000-0002-6827-8055
Mengmeng YangThe First Medical Centre, Chinese PLA General Hospital, Beijing, China.ORCID 0000-0003-4770-0648
Siqian LuBeidou Academic & Research Center, Beidou Life Science, Guangzhou, China.ORCID 0009-0003-2198-3130
Zhichao SunBeidou Academic & Research Center, Beidou Life Science, Guangzhou, China.ORCID 0000-0003-0662-7480
Feihu ZhouThe First Medical Centre, Chinese PLA General Hospital, Beijing, China.ORCID 0000-0001-6154-013X
Zhirong QianBeidou Academic & Research Center, Beidou Life Science, Guangzhou, China.ORCID 0000-0003-1633-4120
Hongjun KangThe First Medical Centre, Chinese PLA General Hospital, Beijing, China.ORCID 0000-0002-5269-9082

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn recent epochs, the field of critical medicine has experienced significant advancements due to the integration of artificial intelligence (AI). Specifically, AI robots have evolved from theoretical concepts to being actively implemented in clinical trials and applications. The intensive care unit (ICU), known for its reliance on a vast amount of medical information, presents a promising avenue for the deployment of robotic AI, anticipated to bring substantial improvements to patient care.

objectiveThis review aims to comprehensively summarize the current state of AI robots in the field of critical care by searching for previous studies, developments, and applications of AI robots related to ICU wards. In addition, it seeks to address the ethical challenges arising from their use, including concerns related to safety, patient privacy, responsibility delineation, and cost-benefit analysis.

methodsFollowing the scoping review framework proposed by Arksey and O'Malley and the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we conducted a scoping review to delineate the breadth of research in this field of AI robots in ICU and reported the findings. The literature search was carried out on May 1, 2023, across 3 databases: PubMed, Embase, and the IEEE Xplore Digital Library. Eligible publications were initially screened based on their titles and abstracts. Publications that passed the preliminary screening underwent a comprehensive review. Various research characteristics were extracted, summarized, and analyzed from the final publications.

resultsOf the 5908 publications screened, 77 (1.3%) underwent a full review. These studies collectively spanned 21 ICU robotics projects, encompassing their system development and testing, clinical trials, and approval processes. Upon an expert-reviewed classification framework, these were categorized into 5 main types: therapeutic assistance robots, nursing assistance robots, rehabilitation assistance robots, telepresence robots, and logistics and disinfection robots. Most of these are already widely deployed and commercialized in ICUs, although a select few remain under testing. All robotic systems and tools are engineered to deliver more personalized, convenient, and intelligent medical services to patients in the ICU, concurrently aiming to reduce the substantial workload on ICU medical staff and promote therapeutic and care procedures. This review further explored the prevailing challenges, particularly focusing on ethical and safety concerns, proposing viable solutions or methodologies, and illustrating the prospective capabilities and potential of AI-driven robotic technologies in the ICU environment. Ultimately, we foresee a pivotal role for robots in a future scenario of a fully automated continuum from admission to discharge within the ICU.

conclusionsThis review highlights the potential of AI robots to transform ICU care by improving patient treatment, support, and rehabilitation processes. However, it also recognizes the ethical complexities and operational challenges that come with their implementation, offering possible solutions for future development and optimization.

Indexed as

Artificial IntelligenceCritical CareRoboticsHumansIntensive Care UnitsAIartificial intelligencecritical care medicineICUintensive care unitrobotics

Identifiers

PMID38801765
PMCPMC11165292

What OpenQuestion holds

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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.