ReviewBMC medical informatics and decision making2026
Artificial intelligence and medical futility.
Review in BMC medical informatics and decision making, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundDetermining when medical treatment is futile is conceptually, empirically, and ethically disputed. This creates challenges for patients, families, doctors, healthcare, and legal systems. Amid such disputes, there is still a practical need to resolve futility questions in individual cases. Can artificial intelligence (AI) be ethically and effectively used to help with such decisions?
methodsWe adopted a critical narrative review method. We first surveyed existing scholarship on the ethics of medical futility to identify the main positions in ongoing futility debates. We then surveyed existing or potential medical AI devices to identify whether such tools might be used to help address these debates or their practical upshots. Finally, we philosophically analysed whether such tools ought to be used, identifying and weighing reasons using analytic argument, applying relevant ethical concepts, and philosophical principles, such as respect for autonomy, beneficence, non-maleficence, and justice.
resultsWe found that there are some key challenges or risks in using AI for such purposes, for example, using AI may exacerbate the problem of self-fulfilling prophecies in futility determination by absorbing predicted outcomes as data. Nevertheless, under certain conditions, medical AI could ethically be used to prevent or help resolve futility disputes in healthcare decision-making.
conclusionsAI could ethically contribute to preventing or resolving futility disputes depending on how AI is integrated and regulated in end-of-life care.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.