Evidence map›Paper›PMID 39556140›Full record

ArticleCurrent urology reports2024

Artificial Intelligence as a Tool for Creating Patient Visit Summary: A Scoping Review and Guide to Implementation in an Erectile Dysfunction Clinic.

Supanut Lumbiganon, Elia Abou Chawareb, Muhammed A Moukhtar Hammad, Babak Azad, Dillan Shah, Faysal A Yafi

Abstract readScoping Review
PubMed Publisher
In one paragraph

Article in Current urology reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

  1. Pooled it
  2. The Use of Ambient Dictation Artificial Intelligence in Clinical Spaces in Surgery: A Scoping Review.World journal of otorhinolaryngology - head and neck surgery · 2026
    Review
  3. Review
  4. 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

6 authors.

Supanut LumbiganonDepartment of Urology, University of California, Irvine, CA, USA.
Elia Abou ChawarebDepartment of Urology, University of California, Irvine, CA, USA.
Muhammed A Moukhtar HammadDepartment of Urology, University of California, Irvine, CA, USA.
Babak AzadDepartment of Urology, University of California, Irvine, CA, USA.
Dillan ShahDepartment of Urology, University of California, Irvine, CA, USA.
Faysal A YafiDepartment of Urology, University of California, Irvine, CA, USA. fyafi@hs.uci.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewIn modern healthcare, the integration of artificial intelligence (AI) has revolutionized clinical practices, particularly in data management and patient visit summary creation. Manual creation of patient summary is repetitive, time-consuming, prone to errors, and increases clinicians' workload. AI, through voice recognition and Natural Language Processing (NLP), can automate this task more accurately and efficiently. Erectile dysfunction (ED) clinics, which deal with specific pattern of conditions together with an involvement of broader systemic issues, can greatly benefit from AI-driven patient summary. This scoping review examined the evidence on AI-generated patient summary and evaluated their implementation in ED clinics. RECENT

findingsA total of 381 articles were initially identified, 11 studies were included for the analysis. These studies showcased various methodologies, such as AI-assisted clinical notes and NLP algorithms. Most studies have demonstrated the ability of AI to be used in real life clinical scenarios. Major electronic health record platforms are also integrating AI to their system. However, to date, no studies have specifically addressed AI for patient summary creation in ED clinics.

Indexed as

Artificial IntelligenceErectile DysfunctionElectronic Health RecordsHumansMaleNatural Language ProcessingAIArtificial intelligenceErectile dysfunctionNoteSummaryVisit

Identifiers

PMID39556140

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.