Evidence map›Paper›PMID 37373940›Full record

ReviewJournal of personalized medicine2023

A Review of the Role of Artificial Intelligence in Healthcare.

Ahmed Al Kuwaiti, Khalid Nazer, Abdullah Al-Reedy, Shaher Al-Shehri, Afnan Al-Muhanna, Arun Vijay Subbarayalu, Dhoha Al Muhanna, Fahad A Al-Muhanna

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of personalized medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 263 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
263citing papers in PubMed, 8 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

263 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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203 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

8 authors.

Ahmed Al KuwaitiDepartment of Dental Education, College of Dentistry, Deanship of Quality and Academic Accreditation, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia.ORCID 0000-0002-0390-1977
Khalid NazerDepartment of Information and Technology, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia.
Abdullah Al-ReedyDepartment of Information and Technology, Family and Community Medicine Department, Family and Community Medicine Centre, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia.
Shaher Al-ShehriFaculty of Medicine, Family and Community Medicine Department, Family and Community Medicine Centre, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia.
Afnan Al-MuhannaBreast Imaging Division, Department of Radiology, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia.ORCID 0000-0002-9898-0881
Arun Vijay SubbarayaluQuality Studies and Research Unit, Vice Deanship of Quality, Deanship of Quality and Academic Accreditation, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia.ORCID 0000-0002-5758-118X
Dhoha Al MuhannaNDirectorate of Quality and Patient Safety, Family and Community Medicine Center, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia.
Fahad A Al-MuhannaNephrology Division, Department of Internal Medicine, Faculty of Medicine, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia.ORCID 0000-0003-2169-8391

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) applications have transformed healthcare. This study is based on a general literature review uncovering the role of AI in healthcare and focuses on the following key aspects: (i) medical imaging and diagnostics, (ii) virtual patient care, (iii) medical research and drug discovery, (iv) patient engagement and compliance, (v) rehabilitation, and (vi) other administrative applications. The impact of AI is observed in detecting clinical conditions in medical imaging and diagnostic services, controlling the outbreak of coronavirus disease 2019 (COVID-19) with early diagnosis, providing virtual patient care using AI-powered tools, managing electronic health records, augmenting patient engagement and compliance with the treatment plan, reducing the administrative workload of healthcare professionals (HCPs), discovering new drugs and vaccines, spotting medical prescription errors, extensive data storage and analysis, and technology-assisted rehabilitation. Nevertheless, this science pitch meets several technical, ethical, and social challenges, including privacy, safety, the right to decide and try, costs, information and consent, access, and efficacy, while integrating AI into healthcare. The governance of AI applications is crucial for patient safety and accountability and for raising HCPs' belief in enhancing acceptance and boosting significant health consequences. Effective governance is a prerequisite to precisely address regulatory, ethical, and trust issues while advancing the acceptance and implementation of AI. Since COVID-19 hit the global health system, the concept of AI has created a revolution in healthcare, and such an uprising could be another step forward to meet future healthcare needs.

Indexed as

artificial intelligenceethicsgovernancehealthcare

Identifiers

PMID37373940
PMCPMC10301994

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.