Evidence map›Paper›PMID 39009918›Full record

ReviewDigestive diseases and sciences2024

Ethical Implications of Artificial Intelligence in Gastroenterology: The Co-pilot or the Captain?

Nishant Aggarwal, David A Drew, Ravi B Parikh, Sushovan Guha

Abstract readReview
PubMed Publisher
In one paragraph

Review in Digestive diseases and sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed, 1 synthesis or guideline 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

4 authors.

Nishant AggarwalDepartment of Internal Medicine, William Beaumont University Hospital, Royal Oak, MI, USA.
David A DrewClinical & Translational Epidemiology Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Ravi B ParikhPerelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Sushovan GuhaGastroenterology and Hepatology, Houston Regional Gastroenterology Institute (HRGI), Houston, TX, USA. sguha@hrgastro.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Though artificial intelligence (AI) is being widely implemented in gastroenterology (GI) and hepatology and has the potential to be paradigm shifting for clinical practice, its pitfalls must be considered along with its advantages. Currently, although the use of AI is limited in practice to supporting clinical judgment, medicine is rapidly heading toward a global environment where AI will be increasingly autonomous. Broader implementation of AI will require careful ethical considerations, specifically related to bias, privacy, and consent. Widespread use of AI raises concerns related to increasing rates of systematic errors, potentially due to bias introduced in training datasets. We propose that a central repository for collection and analysis for training and validation datasets is essential to overcoming potential biases. Since AI does not have built-in concepts of bias and equality, humans involved in AI development and implementation must ensure its ethical use and development. Moreover, ethical concerns regarding data ownership and health information privacy are likely to emerge, obviating traditional methods of obtaining patient consent that cover all possible uses of patient data. The question of liability in case of adverse events related to use of AI in GI must be addressed among the physician, the healthcare institution, and the AI developer. Though the future of AI in GI is very promising, herein we review the ethical considerations in need of additional guidance informed by community experience and collective expertise.

Indexed as

Artificial IntelligenceGastroenterologyConfidentialityHumansInformed ConsentData ownershipMachine learningMedical ethics

Identifiers

PMID39009918

What OpenQuestion holds

Textmetadata
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.