Evidence map›Paper›PMID 41477060›Full record

ArticleMedical review (2021)2025

The AI doctor will see you soon: from assistants to autonomous practitioners.

Tianshu Gu, Xia Meng, Yongjun Wang, Weikuan Gu

Abstract read
In one paragraph

Article in Medical review (2021), 2025. 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

4 authors.

Tianshu GuDepartment of Clinical Pharmacy and Translational Science, University of Tennessee Health Science Center, Memphis, TN, USA.
Xia MengDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, PR China.
Yongjun WangDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, PR China.
Weikuan GuDepartment of Orthopedic Surgery and BME-Campbell Clinic, University of Tennessee Health Science Centre, Memphis, TN, USA.ORCID https://orcid.org/0000-0003-1112-8088

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial Intelligence (AI) is bringing an unprecedented evolution in human history. As it develops, the utilization of AI in clinical practice becomes one of the hot topics that attracts the attention of the medical field as well as the public. While we know that AI will be heavily involved in the medical system, a critical question is what we expect for the future AI medical doctor. To answer this question, it is important to understand that the developing patterns of any other discovery and industrialization do not fit the pattern of AI development, because it acts more like a human instead of simply being a machine or tool. Thus, AI doctors function like human doctors to provide patient-centered reasoning, intellectual judgment, and ethical decision-making rather than just mechanical data processing. Here we present such a likely development process, including current AI status, expected AI doctors, challenges, and future directions.

Indexed as

AIdoctorethicsmedical roboticspersonalizationpopulation

Identifiers

PMID41477060
PMCPMC12752732

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.