Evidence map›Paper›PMID 40055745›Full record

ArticleBMC oral health2025

Artificial intelligence-based chatbot assistance in clinical decision-making for medically complex patients in oral surgery: a comparative study.

Alanur Çiftçi Şişman, Ahmet Hüseyin Acar

Abstract readComparative Study
In one paragraph

Article in BMC oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Review
  2. Performance Comparison of a Domain-Specific Chatbot and General-Purpose Chatbots in Dental Traumatology.Dental traumatology : official publication of International Association for Dental Traumatology · 2026
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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

2 authors.

Alanur Çiftçi ŞişmanHamidiye Faculty of Dental Medicine, Department of Oral and Maxillofacial Surgery, University of Health Sciences, Istanbul, Türkiye. alanurciftci@gmail.com.ORCID http://orcid.org/0000-0002-3121-6467
Ahmet Hüseyin AcarFaculty of Dentistry, Department of Oral and Maxillofacial Surgery, Istanbul Medeniyet University, Istanbul, Türkiye.ORCID http://orcid.org/0000-0002-0409-8290

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimThis study aims to evaluate the potential of AI-based chatbots in assisting with clinical decision-making in the management of medically complex patients in oral surgery. MATERIALS AND

methodsA team of oral and maxillofacial surgeons developed a pool of open-ended questions de novo. The validity of the questions was assessed using Lawshe's Content Validity Index. The questions, which focused on systemic diseases and common conditions that may raise concerns during oral surgery, were presented to ChatGPT 3.5 and Claude-instant in two separate sessions, spaced one week apart. Two experienced maxillofacial surgeons, blinded to the chatbots, assessed the responses for quality, accuracy, and completeness using a modified DISCERN tool and Likert scale. Intraclass correlation, Mann-Whitney U test, skewness, and kurtosis coefficients were employed to compare the performances of the chatbots.

resultsMost responses were high quality: 86% and 79.6% for ChatGPT, and 81.25% and 89% for Claude-instant in sessions 1 and 2, respectively. In terms of accuracy, ChatGPT had 92% and 93.4% of its responses rated as completely correct in sessions 1 and 2, respectively, while Claude-instant had 95.2% and 89%. For completeness, ChatGPT had 88.5% and 86.8% of its responses rated as adequate or comprehensive in sessions 1 and 2, respectively, while Claude-instant had 95.2% and 86%.

conclusionOngoing software developments and the increasing acceptance of chatbots among healthcare professionals hold promise that these tools can provide rapid solutions to the high demand for medical care, ease professionals' workload, reduce costs, and save time.

Indexed as

Artificial IntelligenceClinical Decision-MakingOral Surgical ProceduresSurgery, OralGenerative Artificial IntelligenceHumansSurveys and QuestionnairesArtificial intelligenceChatbotChatGPTClinical decision-makingDigital healthMaxillofacial surgeryOral surgery

Identifiers

PMID40055745
PMCPMC11887094

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.