Evidence map›Paper›PMID 37221540›Full record

ArticlePhilosophy, ethics, and humanities in medicine : PEHM2023

Reconciling art and science in the era of personalised medicine: the legacy of George Canguilhem.

Gianmarco Contino

Open access · goldAbstract read
In one paragraph

Article in Philosophy, ethics, and humanities in medicine : PEHM, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 41% of its field
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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 1 institution in 1 country.

Gianmarco ContinoVon Hügel Institute, University of Cambridge, Cambridge, UK. g.contino@bham.ac.uk.ORCID http://orcid.org/0000-0001-5874-0405
University of Cambridge · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBiomedicine, i.e. the application of basic sciences to medicine, has become the cornerstone for the study of etiopathogenesis and treatment of diseases. Biomedicine has enormously contributed to the progress of medicine and healthcare and has become the preferred approach to medical problems in the West. The developments in statistical inference and machine learning techniques have provided the foundation for personalised medicine where clinical management can be fully informed by biomedicine. The deployment of precision medicine may impact the autonomy and self-normativity of the patients. Understanding the relationship between biomedicine and medical practice can help navigate the benefits and challenges offered by precision medicine.

methodsConventional content analysis was applied to "Le Normal and le Pathologique" (Canguilhem G. The Normal and the Pathological. Princeton: Princeton University Press; 1991) and further investigated with respect to its relationship with techne and precision medicine using PubMed and Google Scholar and the Standford Encyclopedia of Philosophy to search for the following keywords singularly or in combination: "Canguilhem", "techne", "episteme", "precision medicine", "machine learning AND medicine".

resultsThe Hippocratic concept of techne accounts for many characteristics of medical knowledge and practice. The advances of biomedicine, experimental medicine and, more recently, machine learning offer, in contrast, the model of a medicine based purely on episteme. I argue that Canguilhem medical epistemology establishes a framework where episteme and data-driven medicine is compatible with the promotion of patient's autonomy and self-normativity.

conclusionsCanguilhem's medical epistemology orders the relationship of applied medicine with experimental sciences, ethics and social sciences. It provides guidance to define the scope of medicine and the boundaries of medicalization of healthy life. Finally, it sets an agenda for a safe implementation of machine learning in medicine.

Indexed as

Biomedical ResearchLepidopteraAnimalsHealth FacilitiesHealth OccupationsHealth StatusHumansPrecision MedicineEpistemology (K01.468)Experimental Medicine (H01.770.644.145)Medical Philosophy (K01.752.667)

Identifiers

PMID37221540
PMCPMC10207805
OpenAlexW4377861233

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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.