Evidence map›Paper›PMID 39663266›Full record

ReviewCurrent urology reports2024

Artificial Intelligence-Based Clinical Decision-Making in Erectile Dysfunction: a Narrative Review.

Ahmet Serdar Teoman, Ege Can Serefoglu

Abstract readReview
PubMed Publisher
In one paragraph

Review 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 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. Review
  2. Review
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

2 authors.

Ahmet Serdar TeomanUrology Clinic, 7M Private Hospital, Trabzon, Turkey.
Ege Can SerefogluDepartment of Urology, Biruni University School of Medicine, Fulya Sok. No:2, Sisli, Istanbul, 34365, Turkey. egecanserefoglu@hotmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewArtificial Intelligence (AI) has great potential in erectile dysfunction (ED) diagnosis and treatment. This review aims to summarize AI-based clinical decision-making in ED. RECENT

findingsBased on the literature search, forty-seven articles related to AI and ED were analyzed and their findings were summarized. AI may help diagnose ED and offer treatment for it. Developing AI chatbots may also be beneficial for ED patients who are embarrassed to seek treatment. However, there are deficiencies in AI programs and a lack of accuracy in offering precise diagnoses and treatments for ED. AI technology integrates positively into ED clinical decision-making processes and needs progressive research to gain precision and efficiency.

Indexed as

Artificial IntelligenceClinical Decision-MakingErectile DysfunctionHumansMaleArtificial intelligenceChatGPTDeep neural networksErectile dysfunctionMachine learning

Identifiers

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.