Evidence map›Paper›PMID 37705603›Full record

ReviewFrontiers in artificial intelligence2023

Artificial intelligence in clinical medicine: catalyzing a sustainable global healthcare paradigm.

Gokul Krishnan, Shiana Singh, Monika Pathania, Siddharth Gosavi, Shuchi Abhishek, Ashwin Parchani, Minakshi Dhar

Abstract readReview
In one paragraph

Review in Frontiers in artificial intelligence, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 113 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
113citing papers in PubMed, 7 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

113 citing papers in PubMed, 7 syntheses or guidelines pooled it.

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  19. Recent Advances in AI and GenAI for Health Informatics.Healthcare (Basel, Switzerland) · 2026
    Review
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53 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

7 authors.

Gokul Krishnan *Department of Internal Medicine, Kasturba Medical College, Manipal, India.
Shiana Singh *Department of Emergency Medicine, All India Institute of Medical Sciences, Rishikesh, India.
Monika Pathania *Department of Geriatric Medicine, All India Institute of Medical Sciences, Rishikesh, India.
Siddharth GosaviDepartment of Internal Medicine, Kasturba Medical College, Manipal, India.
Shuchi AbhishekDepartment of Internal Medicine, Kasturba Medical College, Manipal, India.
Ashwin ParchaniDepartment of Geriatric Medicine, All India Institute of Medical Sciences, Rishikesh, India.
Minakshi DharDepartment of Geriatric Medicine, All India Institute of Medical Sciences, Rishikesh, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the demand for quality healthcare increases, healthcare systems worldwide are grappling with time constraints and excessive workloads, which can compromise the quality of patient care. Artificial intelligence (AI) has emerged as a powerful tool in clinical medicine, revolutionizing various aspects of patient care and medical research. The integration of AI in clinical medicine has not only improved diagnostic accuracy and treatment outcomes, but also contributed to more efficient healthcare delivery, reduced costs, and facilitated better patient experiences. This review article provides an extensive overview of AI applications in history taking, clinical examination, imaging, therapeutics, prognosis and research. Furthermore, it highlights the critical role AI has played in transforming healthcare in developing nations.

Indexed as

clinical medicinedeep learninginternal medicinemachine learningneural networks

Identifiers

PMID37705603
PMCPMC10497111

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.