Evidence map›Paper›PMID 39179908›Full record

ArticleInternational journal of impotence research2024

Can AI chatbots accurately answer patient questions regarding vasectomies?

Edwin Mouhawasse, Christopher W Haff, Preet Kumar, Benjamin Lack, Kevin Chu, Utsav Bansal, Justin M Dubin

Abstract read
PubMed Publisher
In one paragraph

Article in International journal of impotence research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

7 authors.

Edwin MouhawasseCharles E. Schmidt Florida Atlantic University College of Medicine, Boca Raton, FL, USA. emouhawasse2021@health.fau.edu.ORCID http://orcid.org/0009-0006-4083-4650
Christopher W HaffCharles E. Schmidt Florida Atlantic University College of Medicine, Boca Raton, FL, USA.ORCID http://orcid.org/0009-0009-6013-9585
Preet KumarCharles E. Schmidt Florida Atlantic University College of Medicine, Boca Raton, FL, USA.
Benjamin LackCharles E. Schmidt Florida Atlantic University College of Medicine, Boca Raton, FL, USA.
Kevin ChuAdvanced Urology, Los Angeles, CA, USA.ORCID http://orcid.org/0000-0002-4436-3220
Utsav BansalDivision of Urology, Department of Surgery, Memorial Healthcare System, Hollywood, FL, 33021, USA.
Justin M DubinDivision of Urology, Department of Surgery, Memorial Healthcare System, Hollywood, FL, 33021, USA.ORCID http://orcid.org/0000-0001-7401-6206

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial Intelligence (AI) has revolutionized the healthcare industry. There have been limited studies assessing AI model efficacy and accuracy in urology. To our knowledge, there is a lack in research looking at one of the most common urological procedures: the vasectomy. Ten frequently asked questions regarding vasectomies were individually entered into three different AI sources (ChatGPT, Bard & Bing) using free interfaces available to consumers. The responses were critically analyzed by three urologists and graded on a scale of 1 to 4 for clarity, accuracy, and evidence-based information, with 1 being the best and 4 being the worst. ChatGPT had the best average rating per question at 1.367, followed by Bard at 2.167 and Bing at 1.800(p = 0.000083). ChatGPT was found to provide significantly more satisfactory answers than both Bard (p = 0.00005) and Bing (p = 0.03988). The difference between Bard and Bing however was found to be insignificant (p = 0.09651). Overall, our study shows that AI Chatbots may provide mostly accurate information on frequently asked questions regarding vasectomies and is a reasonable resource for patients interested in the procedure to use. ChatGPT is the most accurate and concise of the chatbots assessed.

Identifiers

PMID39179908

What OpenQuestion holds

Textmetadata
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.