Evidence map›Paper›PMID 33925767›Full record

ReviewJournal of clinical medicine2021

Artificial Intelligence and Its Impact on Urological Diseases and Management: A Comprehensive Review of the Literature.

B M Zeeshan Hameed, Aiswarya V L S Dhavileswarapu, Syed Zahid Raza, Hadis Karimi, Harneet Singh Khanuja, Dasharathraj K Shetty, Sufyan Ibrahim, Milap J Shah, Nithesh Naik, Rahul Paul and 2 more

Abstract readReview
In one paragraph

Review in Journal of clinical medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
53citing 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

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

  1. Pooled it
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  7. State of the art review of AI in renal imaging.Abdominal radiology (New York) · 2025
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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

12 authors.

B M Zeeshan HameedDepartment of Urology, Kasturba Medical College Manipal, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India.
Aiswarya V L S DhavileswarapuDepartment of Electronics and Communication, GITAM University, Gandhi Nagar, Rushi Konda, Visakhapatnam 530045, Andhra Pradesh, India.
Syed Zahid RazaDepartment of Urology, Dr. B.R. Ambedkar Medical College, Bengaluru 560045, Karnataka, India.
Hadis KarimiManipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India.
Harneet Singh KhanujaDepartment of Information and Communication Technology, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India.
Dasharathraj K ShettyDepartment of Humanities and Management, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India.ORCID 0000-0002-5021-4029
Sufyan IbrahimiTRUE (International Training and Research in Uro-Oncology and Endourology) Group, Manipal 576104, Karnataka, India.
Milap J ShahDepartment of Urology, Kasturba Medical College Manipal, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India.
Nithesh NaikiTRUE (International Training and Research in Uro-Oncology and Endourology) Group, Manipal 576104, Karnataka, India.ORCID 0000-0003-0356-7697
Rahul PaulDepartment of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA.
Bhavan Prasad RaiDepartment of Urology, Freeman Hospital, Newcastle NE7 7DN, UK.
Bhaskar K SomaniDepartment of Urology, Kasturba Medical College Manipal, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India.ORCID 0000-0002-6248-6478

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent advances in artificial intelligence (AI) have certainly had a significant impact on the healthcare industry. In urology, AI has been widely adopted to deal with numerous disorders, irrespective of their severity, extending from conditions such as benign prostate hyperplasia to critical illnesses such as urothelial and prostate cancer. In this article, we aim to discuss how algorithms and techniques of artificial intelligence are equipped in the field of urology to detect, treat, and estimate the outcomes of urological diseases. Furthermore, we explain the advantages that come from using AI over any existing traditional methods.

Indexed as

artificial intelligencebladder cancerendourologyfertilityhydronephrosiskidney stone diseasemachine learningpediatric urologyprostate cancerrenal cell carcinomareproductive urologyurinary incontinenceurinary refluxurolithiasisurology

Identifiers

PMID33925767
PMCPMC8123407

What OpenQuestion holds

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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.