Revolutionizing healthcare: the role of artificial intelligence in clinical practice

Shuroug A. Alowais; Sahar S. Alghamdi; Nada Alsuhebany; Tariq Alqahtani; Abdulrahman Alshaya

doi:10.1186/s12909-023-04698-z

Revolutionizing healthcare: the role of artificial intelligence in clinical practice

Shuroug A. Alowais, Sahar S. Alghamdi, Nada Alsuhebany, Tariq Alqahtani, Abdulrahman Alshaya, Sumaya N. Almohareb, Atheer Aldairem, Mohammed Alrashed, Khalid Bin Saleh, Hisham A. Badreldin, Majed S. Al Yami, Shmeylan Al Harbi, Abdulkareem Albekairy

BioMed Central (2023) • Volume 23, Issue 1, Pages 689-689

SynthesisNarrativeReviewPDF AvailableGrade Eligible

Overall Assessment

Weak Methodological Quality

Assessment created by PaperScorers Medical AI v0.1.0 on Dec 14, 2025

D-

39/100

Key Takeaways

•Narrative review; English-only searches and no PRISMA/registration.
•Provides broad examples; no formal risk-of-bias or quantitative synthesis.
•COI none; no funding; AI tool use (Chatsonic/GPT-4) disclosed.
•Useful primer but limited methodological rigour and reproducibility.

Conclusion

A broad, educational narrative overview of AI in healthcare; transparent but non-systematic, so interpret claims cautiously.

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Quality Dimensions

Bias & Integrity

COI handling, outcome switching, selective reporting

C-55

Methods Rigour

Protocol clarity, sampling, controls

F25

External Validity

Generalisability, setting, population

D+50

Transparency & Reproducibility

Data/code/materials availability, preregistration

D-30

Significance & Novelty

Contribution vs prior art; context if known

D40

Statistical Validity

Models, assumptions, multiplicity, CI priority

F20

Integrity & Transparency

Integrity checks

P-hacking risk?

?

None suspected

Signs of selective hypothesis testing or analysis choices that could inflate false positive rates.

Outcome switching?

?

None suspected

Evidence that primary outcomes were changed during or after the study, potentially distorting results.

Conflict of interest?

?

None suspected

Authors have financial or other relationships that could bias research findings.

Data integrity issues?

?

None suspected

Concerns about the accuracy, completeness, or authenticity of the reported data.

Open science signals

Research data

?

Not applicable

Raw data used in the analyses is publicly available or accessible upon request.

Analysis code

?

Not applicable

Code or scripts used to analyze the data are shared for reproducibility.

Study materials

?

Not applicable

Protocols, questionnaires, and other materials are publicly available.

Premise

Primary Research Question

What is the current state, benefits, challenges, and future of AI in clinical practice?

Hypothesis is Falsifiable

—Not specified

Review article; no testable hypothesis.

PICO Framework

Population—Not specified

No enrolled population; narrative review.

Intervention—Not specified

No intervention; descriptive synthesis.

Comparison—Not specified

No comparator.

Outcome—Not specified

No prespecified outcomes.

Literature Positioning

Literature Review Balanced

Well covered

Cites diverse AI applications across diagnostics, genomics, treatment, population health, ethics.

Evidence: pp. 3–11

Research Gap Clearly Stated

Well covered

States need to document AI’s role in clinical practice to aid implementation.

Evidence: p. 1 (Abstract)

Stated Contribution Clear

Well covered

Promises comprehensive overview of AI in clinical practice and challenges.

Evidence: p. 1 (Abstract)

Study Provenance

Peer reviewed venueGrant funding disclosedNo conflicts declared5 affiliations listed

Authors & Affiliations

King Saud bin Abdulaziz University for Health Sciences; King Abdullah International Medical Research Center; National Guard Health Affairs, Riyadh, Saudi Arabia.

Funding Statement

This research did not receive any specific grant from funding agencies.

Conflicts of Interest

The authors declare that they have no competing interests.

Peer Review

✓Published in BMC Medical Education, a peer‑reviewed journal.

Methodological Assessment

All design modules are marked as not applicable. Use the accordion below to review their details.

Modules without applicable checklist items (10)

These designs were fully marked as not applicable but remain available for reference.

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Study Overview

Study Design

Narrative Review

Primary classification used to evaluate this research.

Population

Narrative review of AI in healthcare; no primary participants.

Brief summary of who or what was studied.

Pre-registration

Not registered

Indicates whether the protocol or trial was registered before data collection.

Primary Outcome

Primary outcome was not pre-specified.

Reviewer Notes

Classified as a narrative review; descriptive synthesis with limited methods and no SR/MA protocol.

Publication Details

DOI

10.1186/s12909-023-04698-z

Published

September 22, 2023

Citations

2127 citations

FWCI

111.29

External Resources

DOI Link OpenAlex

Disclaimer: This assessment is generated by AI and should not be the sole basis for clinical or research decisions. Always review the original paper and consult with domain experts.

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