An exploratory study on the potential of ChatGPT as an AI-assisted diagnostic tool for visceral leishmaniasis

Visceral leishmaniasis (VL) is a severe parasitic disease that poses significant diagnostic challenges due to its complex presentation and the necessity for comprehensive diagnostic methods. This exploratory study investigates the potential of Chat Generative Pre-trained Transformer (ChatGPT)/GPT-4, an artificial intelligence (AI) chatbot, in assisting the diagnostic process for VL. We evaluated the diagnostic accuracy of ChatGPT/GPT-4 in generating differential diagnosis lists for eight clinical vignette cases of VL, authored by a Brazilian infectious disease doctor. Our findings reveal that ChatGPT/GPT-4 included VL in the top five differential diagnoses in 75% of the cases (95% confidence interval [CI]: 40.1 – 93.7%) and identified VL as the top diagnosis in 50% of the cases (95% CI: 30.3 – 86.5%). These results underscore the high potential of ChatGPT/GPT-4 as an AI-assisted diagnostic tool, which is capable of providing accurate differential diagnoses and assisting healthcare professionals in resource-limited settings. The study highlights the broader applicability of AI chatbots in medical diagnostics, not only for common conditions but also for specialized and less prevalent diseases like VL. By integrating AI tools into the diagnostic workflow, healthcare providers can enhance their diagnostic accuracy and efficiency, ultimately improving patient outcomes. This research contributes to the growing body of evidence supporting the utility of AI in healthcare and underscores the need for further studies to validate these findings across larger and more diverse clinical scenarios.

Authors

Publication Details

Journal
Artificial Intelligence in Health
Published
2024-10-16
DOI
https://doi.org/10.36922/aih.3930
Citations
2
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.24
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article

An exploratory study on the potential of ChatGPT as an AI-assisted diagnostic tool for visceral leishmaniasis

Paulo Adriano Schwingel, Flávia Emí­lia Cavalcante Valença Fernandes, Bruno Bavaresco Gambassi, Samuel Ricarte de Aquino et al.
2 citations
Artificial Intelligence in Health
Artificial Intelligence in Healthcare and Education
0.24
article

An exploratory study on the potential of ChatGPT as an AI-assisted diagnostic tool for visceral leishmaniasis

Paulo Adriano Schwingel, Flávia Emí­lia Cavalcante Valença Fernandes, Bruno Bavaresco Gambassi, Samuel Ricarte de Aquino, Maria Jacqueline Silva Ribeiro, Daniela Conceição Gomes Gonçalves e Silva, Pedro Paulo Ramos da Silva, Ricardo Kenji Shiosaki, Paula Andreatta Maduro, Paulo Gustavo Serafim de Carvalho, Amanda Alves Marcelino da Silva, Raquel M. Gonçalves, Dino Schwingel, R Pereira, Paulo Ditarso Maciel Júnior, Aline Rafaela Soares da Silva
article en
2 citations

Abstract

Visceral leishmaniasis (VL) is a severe parasitic disease that poses significant diagnostic challenges due to its complex presentation and the necessity for comprehensive diagnostic methods. This exploratory study investigates the potential of Chat Generative Pre-trained Transformer (ChatGPT)/GPT-4, an artificial intelligence (AI) chatbot, in assisting the diagnostic process for VL. We evaluated the diagnostic accuracy of ChatGPT/GPT-4 in generating differential diagnosis lists for eight clinical vignette cases of VL, authored by a Brazilian infectious disease doctor. Our findings reveal that ChatGPT/GPT-4 included VL in the top five differential diagnoses in 75% of the cases (95% confidence interval [CI]: 40.1 – 93.7%) and identified VL as the top diagnosis in 50% of the cases (95% CI: 30.3 – 86.5%). These results underscore the high potential of ChatGPT/GPT-4 as an AI-assisted diagnostic tool, which is capable of providing accurate differential diagnoses and assisting healthcare professionals in resource-limited settings. The study highlights the broader applicability of AI chatbots in medical diagnostics, not only for common conditions but also for specialized and less prevalent diseases like VL. By integrating AI tools into the diagnostic workflow, healthcare providers can enhance their diagnostic accuracy and efficiency, ultimately improving patient outcomes. This research contributes to the growing body of evidence supporting the utility of AI in healthcare and underscores the need for further studies to validate these findings across larger and more diverse clinical scenarios.

Artificial Intelligence in HealthVol. 1(4)
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Artificial Intelligence in Healthcare and Education
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