Evidence map›Paper›PMID 40083589›Full record

ArticleCureus2025

Bioethics Artificial Intelligence Advisory (BAIA): An Agentic Artificial Intelligence (AI) Framework for Bioethical Clinical Decision Support.

Taposh P Dutta Roy

Abstract read
In one paragraph

Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. Review
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

1 author.

Taposh P Dutta RoyResponsible AI, Kaiser Permanente, Oakland, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Healthcare professionals face complex ethical dilemmas in clinical settings in cases involving end-of-life care, informed consent, and surrogate decision-making. These nuanced situations often lead to moral distress among care providers. This paper introduces the Bioethics Artificial Intelligence Advisory (BAIA) framework, a novel and innovative approach that leverages artificial intelligence (AI) to support clinical ethical decision-making. The BAIA framework integrates multiple bioethical approaches, including principlism, casuistry, and narrative ethics, with advanced AI capabilities to provide comprehensive decision support. The framework employs a structured methodology that includes data collection, paradigmatic case review, analysis through "mattering maps," and scenario-based decision reasoning. A detailed analysis of two challenging cases, an end-of-life care decision and a complex conjoined twins case, demonstrates BAIA's potential to harmonize diverse ethical perspectives while reducing the moral burden on healthcare providers. The framework's agentic architecture additionally allows integration with any new and existing ethical AI systems like METHAD, Delphi, and EAIFT, enabling multiframework collaboration. This work also acknowledges limitations related to data quality, bias, and complexity of ethical decisions and proposes mitigation strategies, including standardized databases, fairness algorithms, and maintaining human oversight. Thus, this work represents a significant step toward combining technological advancement in agentic AI with established bioethical principles to improve the quality and consistency of clinical ethical decision-making, thus reducing moral distress for clinicians.

Indexed as

agentic aiaiai bioethicsbioethics frameworkbioethics recommendations

Identifiers

PMID40083589
PMCPMC11906199

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.