Evidence map›Paper›PMID 42147983›Full record

ArticleInfection and drug resistance2026

A Theoretical Framework for

Daniele Roberto Giacobbe, Alessandra Agnese Grossi, Cristina Marelli, Marco Muccio, Sabrina Guastavino, Ylenia Murgia, Sara Mora, Alessio Signori, Nicola Rosso, Mauro Giacomini and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Infection and drug resistance, 2026. 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
–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

0 citing papers in PubMed.

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

13 authors.

Daniele Roberto GiacobbeUO Clinica Malattie Infettive, IRCCS Azienda Ospedaliera Metropolitana, Genoa, Italy.ORCID 0000-0003-2385-1759
Alessandra Agnese GrossiDepartment of Human Sciences and Innovation for the Territory, University of Insubria, Varese, Italy.
Cristina MarelliCESP - INSERM U1018, Oncostat, Labeled Ligue Contre le Cancer, Gustave Roussy, Université Paris-Saclay, Villejuif, France.
Marco MuccioUO Clinica Malattie Infettive, IRCCS Azienda Ospedaliera Metropolitana, Genoa, Italy.ORCID 0009-0004-0297-1019
Sabrina GuastavinoDepartment of Mathematics (DIMA), University of Genoa, Genoa, Italy.
Ylenia MurgiaDepartment of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS), University of Genoa, Genoa, Italy.
Sara MoraUO Information and Communication Technologies, IRCCS Azienda Ospedaliera Metropolitana, Genoa, Italy.
Alessio SignoriDepartment of Health Sciences (DISSAL), Section of Biostatistics, University of Genoa, Genoa, Italy.
Nicola RossoUO Information and Communication Technologies, IRCCS Azienda Ospedaliera Metropolitana, Genoa, Italy.
Mauro GiacominiDepartment of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS), University of Genoa, Genoa, Italy.
Cristina CampiDepartment of Mathematics (DIMA), University of Genoa, Genoa, Italy.
Michele PianaDepartment of Mathematics (DIMA), University of Genoa, Genoa, Italy.
Matteo BassettiUO Clinica Malattie Infettive, IRCCS Azienda Ospedaliera Metropolitana, Genoa, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

General-purpose large language model (LLM)-based chatbots are increasingly used by clinicians to discuss medical problems, including antibiotic prescribing. Their use creates an unprecedented setting for clinical reasoning in which diagnostic and therapeutic thinking becomes dynamically shared between human and machine. Here, we propose a theoretical framework, intended for subsequent empirical assessment, around the concept of

Indexed as

antibiotic prescribingartificial intelligencedeep learninghealthcareinfectionmachine learningnatural language processing

Identifiers

PMID42147983
PMCPMC13179146

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.