Evidence map›Paper›PMID 41675735›Full record

ArticleAnnals of medicine and surgery (2012)2026

Exploring advancements in the management of penile cancer in the era of artificial intelligence and machine learning: a narrative review.

Rao Nouman Ali, Sohaib Irfan, Adeel Anwaar, Muhammad Shahzad Anwar, Inam Ul Haq, Muhammad Irfan, Muhammad Shafi Ghouri, Wajiha Irfan, Aymar Akilimali

Abstract read
In one paragraph

Article in Annals of medicine and surgery (2012), 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

9 authors.

Rao Nouman AliDistrict Headquarter Hospital Khanewal, Punjab, Pakistan.ORCID https://orcid.org/0000-0002-8791-9583
Sohaib IrfanDistrict Headquarter Hospital Khanewal, Punjab, Pakistan.
Adeel AnwaarPakistan Kidney and Liver Institute and Research Center, Lahore, Punjab, Pakistan.ORCID https://orcid.org/0000-0002-6593-8978
Muhammad Shahzad AnwarServices Hospital Lahore, Punjab, Pakistan.
Inam Ul HaqRashid Latif Medical Lahore, Punjab, Pakistan.ORCID https://orcid.org/0009-0003-6747-8906
Muhammad IrfanUniversity Teaching Hospital Gujranwala, Punjab, Pakistan.
Muhammad Shafi GhouriSheikh Zayed Hospital Rahim Yar Khan, Punjab, Pakistan.
Wajiha IrfanDistrict Headquarter Hospital Khanewal, Punjab, Pakistan.
Aymar AkilimaliDepartment of Research, Medical Research Circle (MedReC), Goma, Democratic Republic of Congo.ORCID https://orcid.org/0000-0001-9393-1215

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose of review: This review aims to explore the current state of literature on the use of artificial intelligence (AI) in the management of penile cancer. We examined the various applications of AI in penile cancer, including but not limited to image identification, prediction of treatment results, and patient risk stratification. The review evaluates the current limitations and challenges faced in the implementation of AI in penile cancer management. Recent findings: The present literature emphasized the use of AI using radiomics and pathomics for management strategies and outcomes. Summary: AI has the power to shape the future of penile cancer management by improving diagnostic precision, treatment strategies, and patient outcomes. Literature has shown improved accuracy and quality of current AI models for the detection and treatment of penile cancer. Further research is required to understand its potential and limitations.

Indexed as

artificial intelligencemachine learningpathomicspenile cancerradiomics

Identifiers

PMID41675735
PMCPMC12889263

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.