Evidence map›Paper›PMID 40152019›Full record

ArticleCancer control : journal of the Moffitt Cancer Center

Establishing Artificial Intelligence-Powered Virtual Tumor Board Meetings in Pakistan.

Saqib Raza Khan, Anoud Khan, Aryan Tareen

Abstract read
In one paragraph

Article in Cancer control : journal of the Moffitt Cancer Center. 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

3 authors.

Saqib Raza KhanLondon Regional Cancer Program, London Health Sciences Centre, London, ON, Canada.
Anoud KhanDepartment of Medicine, Ziauddin Medical College, Karachi, Pakistan.ORCID 0009-0009-5913-7064
Aryan TareenDepartment of Medicine, Ziauddin Medical College, Karachi, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Equitable cancer care in low- and middle-income countries is crucial as mortality rates continue to rise. Artificial intelligence (AI)-powered Virtual Tumor Board Meetings (VTBMs) offer an innovative solution that facilitates real-time collaboration between experts to improve patient outcomes. By integrating AI-powered tools, VTBMs can improve diagnostic accuracy and personalize treatment plans using various data sources such as medical images and genomic profiles. In Pakistan, with limited healthcare resources and a high economic burden, the introduction of AI-powered VTBMs has the potential to revolutionize cancer care. This strategic approach will not only address the current challenges in Pakistan, but also serve as a model for improving cancer care in various developing countries.

Indexed as

Artificial IntelligenceNeoplasmsHumansPakistanartificial intelligencelower middle-income countriesPakistanvirtual tumor board

Identifiers

PMID40152019
PMCPMC11951892

What Socratic 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 Socratic graph.