Evidence map›Paper›PMID 42310463›Full record

ArticleNature2026

Towards conversational artificial intelligence for disease management.

Valentin Liévin, Anil Palepu, Wei-Hung Weng, Khaled Saab, David Stutz, Yong Cheng, Kavita Kulkarni, S Sara Mahdavi, Joëlle Barral, Dale R Webster and 10 more

Abstract read
In one paragraph

Article in Nature, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Collaborative AI for precision neurorehabilitation: a roadmap.Journal of neuroengineering and rehabilitation · 2025
    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

20 authors.

Valentin Liévin *Google DeepMind, Mountain View, CA, USA. vlievin@google.com.ORCID http://orcid.org/0000-0002-6096-9564
Anil Palepu *Google Research, Mountain View, CA, USA. apalepu@google.com.ORCID http://orcid.org/0000-0002-4720-8787
Wei-Hung WengGoogle Research, Mountain View, CA, USA.ORCID http://orcid.org/0000-0003-2232-0390
Khaled SaabGoogle DeepMind, Mountain View, CA, USA.ORCID http://orcid.org/0000-0003-1427-0469
David StutzGoogle DeepMind, Mountain View, CA, USA.
Yong ChengGoogle DeepMind, Mountain View, CA, USA.
Kavita KulkarniGoogle Research, Mountain View, CA, USA.
S Sara MahdaviGoogle DeepMind, Mountain View, CA, USA.
Joëlle BarralGoogle DeepMind, Mountain View, CA, USA.
Dale R WebsterGoogle Research, Mountain View, CA, USA.ORCID http://orcid.org/0000-0002-3023-8824
Katherine ChouGoogle Research, Mountain View, CA, USA.
Avinatan HassidimGoogle Research, Mountain View, CA, USA.
Yossi MatiasGoogle Research, Mountain View, CA, USA.ORCID http://orcid.org/0000-0003-3960-6002
James ManyikaGoogle Research, Mountain View, CA, USA.
Ryutaro TannoGoogle DeepMind, Mountain View, CA, USA.ORCID http://orcid.org/0000-0002-8107-6730
Vivek NatarajanGoogle Research, Mountain View, CA, USA.ORCID http://orcid.org/0000-0001-7849-2074
Adam RodmanGoogle Research, Mountain View, CA, USA.
Tao TuGoogle DeepMind, Mountain View, CA, USA.ORCID http://orcid.org/0000-0001-9191-7938
Alan KarthikesalingamGoogle Research, Mountain View, CA, USA. alankarthi@google.com.ORCID http://orcid.org/0009-0000-4958-5976
Mike SchaekermannGoogle Research, Mountain View, CA, USA. mikeshake@google.com.ORCID http://orcid.org/0000-0002-1735-9680

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although large language models have shown promise in diagnostic dialogue

Indexed as

Artificial IntelligenceDisease ManagementLarge Language ModelsCommunicationHumansPhysicians, Primary CarePractice Guidelines as Topic

Identifiers

PMID42310463
PMCPMC13421318

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.