Evidence map›Paper›PMID 40191273›Full record

ArticleMDM policy & practice

Primary Care Provider Preferences Regarding Artificial Intelligence in Point-of-Care Cancer Screening.

Vinayak S Ahluwalia, Marilyn M Schapira, Gary E Weissman, Ravi B Parikh

Abstract read
In one paragraph

Article in MDM policy & practice. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Atencion primaria · 2026
    Pooled it
  2. Article
  3. 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

4 authors.

Vinayak S AhluwaliaPerelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.ORCID https://orcid.org/0000-0002-2227-6644
Marilyn M SchapiraLeonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.ORCID https://orcid.org/0000-0002-3775-9462
Gary E WeissmanLeonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.ORCID https://orcid.org/0000-0001-9588-3819
Ravi B ParikhEmory University School of Medicine, Atlanta, GA, USA.ORCID https://orcid.org/0000-0003-2692-6306

Funding

Improving sepsis care with AI-based clinical decision supportR35GM155262 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI Gary Weissman · 2024 to 2026
$1.2M
Human-Machine Collaborations to Improve Prognosis and Clinical Decision-Making in Advanced CancerK08CA263541 · NCI · UNIVERSITY OF PENNSYLVANIA · PI PARIKH, RAVI BHARAT · 2021 to 2025
$1.2M
Building equitable and feasible clinical decision support tools for population health management of people living with chronic lung diseaseR03HL171424 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI WEISSMAN, GARY · 2024 to 2025
$244k
NCI NIH HHS K08 CA263541NHLBI NIH HHS R03 HL171424NIGMS NIH HHS R35 GM155262
6 · The paper itself

Abstract

Highlights: Clinicians do not feel their undergraduate or graduate medical education has properly prepared them to engage with AI in patient care.We provide a preliminary framework for deploying AI models in primary care-based cancer screening.This framework may have implications for health system governance and provider reimbursement in the age of AI.

Indexed as

artificial intelligencecancer screeningprimary care

Identifiers

PMID40191273
PMCPMC11970086

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.