ArticleIndian journal of pediatrics2026
Assessment of Generative AI Chatbots for Neonatal Diagnostic Reasoning: A Comparative Concordance and Diagnosis Acceptability Analysis.
Article in Indian journal of pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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Who cites it
1 citing paper in PubMed.
- Are artificial intelligence systems ready for pediatric surgical decision-making? A comparative evaluation of large language models versus pediatric surgeons.Pediatric surgery international · 2026Article
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
objectivesTo assess the concordance and diagnosis acceptability of differential diagnoses (DDs) generated by artificial intelligence (AI) chatbots compared to expert neonatology physicians.
methodsThirteen clinical cases from neonatology were developed, each with five expert-defined differential diagnoses. Seven AI chatbots (ChatGPT, Claude, Copilot, Deepseek, Gemini, Grok, Perplexity) were queried to provide their most probable diagnosis along with five DDs per case. Four neonatologists evaluated the chatbot responses. Concordance scores were assigned based on the ranking of chatbot diagnoses against expert-defined diagnoses. Diagnosis acceptability scores were based on the number of DDs deemed clinically acceptable.
resultsThere were no statistically significant differences in the concordance (P = 0.205) or diagnosis acceptability (P = 0.297) scores across the seven chatbots. Chatbots had statistically significant discrepancies when compared to hypothetical values of 5, 4.5, and 4, with none of the chatbots achieving the desired concordance score of 80%. However, in terms of diagnosis acceptability, ChatGPT, Claude, and Grok had scores similar to 90% diagnosis acceptability, while Copilot, Deepseek, Gemini, and Perplexity had 80% diagnosis acceptability.
conclusionsThere were no significant differences in concordance and diagnosis acceptability scores across the seven chatbots. While none achieved the desired concordance of 80%, several models showed near 80-90% diagnosis acceptability. Hence, integration of chatbots should be done with caution.
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