Evidence map›Paper›PMID 39664534›Full record

ArticleFrontiers in public health2024

Physicians' ethical concerns about artificial intelligence in medicine: a qualitative study:

Fatma Kahraman, Aysenur Aktas, Serra Bayrakceken, Tuna Çakar, Hande Serim Tarcan, Bugrahan Bayram, Berk Durak, Yesim Isil Ulman

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 3 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

15 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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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

8 authors.

Fatma KahramanAcibadem University, Departmant of Psychology, Istanbul, Türkiye.
Aysenur AktasAcibadem University, Departmant of Psychology, Istanbul, Türkiye.
Serra BayrakcekenAcibadem University, School of Medicine, Istanbul, Türkiye.
Tuna ÇakarMEF University, Department of Computer Engineering, Istanbul, Türkiye.
Hande Serim TarcanMEF University, Department of Computer Engineering, Istanbul, Türkiye.
Bugrahan BayramAcibadem University, Biomedical Engineering Department, Istanbul, Türkiye.
Berk DurakAcibadem University, School of Medicine, Istanbul, Türkiye.
Yesim Isil UlmanAcibadem University School of Medicine, History of Medicine and Ethics Department, Istanbul, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background/aim: Artificial Intelligence (AI) is the capability of computational systems to perform tasks that require human-like cognitive functions, such as reasoning, learning, and decision-making. Unlike human intelligence, AI does not involve sentience or consciousness but focuses on data processing, pattern recognition, and prediction through algorithms and learned experiences. In healthcare including neuroscience, AI is valuable for improving prevention, diagnosis, prognosis, and surveillance. Methods: This qualitative study aimed to investigate the acceptability of AI in Medicine (AIIM) and to elucidate any technical and scientific, as well as social and ethical issues involved. Twenty-five doctors from various specialties were carefully interviewed regarding their views, experience, knowledge, and attitude toward AI in healthcare. Results: Content analysis confirmed the key ethical principles involved: confidentiality, beneficence, and non-maleficence. Honesty was the least invoked principle. A thematic analysis established four salient topic areas, i.e., Conclusion: The authors conclude that AI should be rationally guided, function transparently, and produce impartial results. It should assist human healthcare professionals collaboratively. This kind of AI will permit fairer, more innovative healthcare which benefits patients and society whilst preserving human dignity. It can foster accuracy and precision in medical practice and reduce the workload by assisting physicians during clinical tasks. AIIM that functions transparently and respects the public interest can be an inspiring scientific innovation for humanity.

Indexed as

Artificial IntelligencePhysiciansQualitative ResearchAdultAttitude of Health PersonnelDecision MakingEthics, MedicalFemaleHumansMaleMiddle Agedartificial intelligencedecision-makingethicshealthcaremedicinequalitative research

Identifiers

PMID39664534
PMCPMC11631923

What OpenQuestion holds

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LicenceCC BY
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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.