Evidence map›Paper›PMID 40352182›Full record

ArticleNarra J2025

Chinese generative AI models (DeepSeek and Qwen) rival ChatGPT-4 in ophthalmology queries with excellent performance in Arabic and English.

Malik Sallam, Israa M Alasfoor, Shahad W Khalid, Rand I Al-Mulla, Amwaj Al-Farajat, Maad M Mijwil, Reem Zahrawi, Mohammed Sallam, Jan Egger, Ahmad S Al-Adwan

Abstract read
In one paragraph

Article in Narra J, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

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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

10 authors.

Malik SallamDepartment of Pathology, Microbiology and Forensic Medicine, School of Medicine, The University of Jordan, Amman, Jordan.
Israa M AlasfoorSection of Ophthalmology, Department of Special Surgery, School of Medicine, The University of Jordan, Amman, Jordan.
Shahad W KhalidSection of Ophthalmology, Department of Special Surgery, School of Medicine, The University of Jordan, Amman, Jordan.
Rand I Al-MullaSection of Ophthalmology, Department of Special Surgery, School of Medicine, The University of Jordan, Amman, Jordan.
Amwaj Al-FarajatSection of Ophthalmology, Department of Special Surgery, School of Medicine, The University of Jordan, Amman, Jordan.
Maad M MijwilCollege of Administration and Economics, Al-Iraqia University, Baghdad, Iraq.
Reem ZahrawiDepartment of Ophthalmology, Mediclinic Parkview Hospital, Mediclinic Middle East, Dubai, United Arab Emirates.
Mohammed SallamDepartment of Pharmacy, Mediclinic Parkview Hospital, Mediclinic Middle East, Dubai, United Arab Emirates.
Jan EggerInstitute for Artificial Intelligence in Medicine (IKIM), Essen University Hospital (AoR), GirardetstraBe, Germany.
Ahmad S Al-AdwanDepartment of Business Technology, Al-Ahliyya Amman University, Amman, Jordan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid evolution of generative artificial intelligence (genAI) has ushered in a new era of digital medical consultations, with patients turning to AI-driven tools for guidance. The emergence of Chinese-developed genAI models such as DeepSeek-R1 and Qwen-2.5 presented a challenge to the dominance of OpenAI's ChatGPT. The aim of this study was to benchmark the performance of Chinese genAI models against ChatGPT-40 and to assess disparities in performance across English and Arabic. Following the METRICS checklist for genAI evaluation, Qwen-2.5, DeepSeek-R1, and ChatGPT-40 were assessed for completeness, accuracy, and relevance using the CLEAR tool in common patient ophthalmology queries. In English, Qwen-2.5 demonstrated the highest overall performance (CLEAR score: 4.43 ± 0.28), outperforming both DeepSeek-R1 (4.3 ± 0.43) and ChatGPT-40 (4.14 ± 0.41), with

Indexed as

Artificial IntelligenceLanguageOphthalmologyChinaEast Asian PeopleGenerative Artificial IntelligenceHumansDeepSeekeye diseaseLLMOpenAIQwen

Identifiers

PMID40352182
PMCPMC12059827

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.