Evidence map›Paper›PMID 34286194›Full record

ArticleFuture healthcare journal2021

The automation of doctors and machines: A classification for AI in medicine (ADAM framework).

Fawz Kazzazi

Abstract read
In one paragraph

Article in Future healthcare journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Fawz KazzaziMason Institute for Medicine, Life Sciences and Law, Edinburgh, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The advances in artificial intelligence (AI) provide an opportunity to expand the frontier of medicine to improve diagnosis, efficiency and management. By extension of being able to perform any task that a human could, a machine that meets the requirements of artificial general intelligence ('strong' AI; AGI) possesses the basic necessities to perform as, or at least qualify to become, a doctor. In this emerging field, this article explores the distinctions between doctors and AGI, and the prerequisites for AGI performing as clinicians. In doing so, it necessitates the requirement for a classification of medical AI and prepares for the development of AGI. With its imminent arrival, it is beneficial to create a framework from which leading institutions can define specific criteria for AGI.

Indexed as

AIartificial intelligenceclinical governancemedical technology

Identifiers

PMID34286194
PMCPMC8285145

What OpenQuestion holds

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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.