Publication Name	World Journal of Methodology
Manuscript ID	92802
Country	India

Received	2024-02-06 04:37
Peer-Review Started	2024-02-06 04:37
To Make the First Decision
Return for Revision	2024-05-24 06:42
Revised	2024-05-29 09:52
Second Decision	2024-06-25 02:51
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2024-06-25 09:45
Articles in Press	2024-06-25 09:45
Publication Fee Transferred
Edit the Manuscript by Language Editor	2024-07-02 05:14
Typeset the Manuscript	2024-07-19 11:17
Publish the Manuscript Online	2024-07-26 08:29

ISSN	2222-0682 (online)
Open Access	This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
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Category	Computer Science, Artificial Intelligence
Manuscript Type	Observational Study
Article Title	Comparative evaluation of artificial intelligence systems' accuracy in providing medical drug dosages: A methodological study
Manuscript Source	Invited Manuscript
All Author List	Swaminathan Ramasubramanian, Sangeetha Balaji, Tejashri Kannan, Naveen Jeyaraman, Shilpa Sharma, Filippo Migliorini, Suhasini Balasubramaniam and Madhan Jeyaraman
ORCID	Author(s) ORCID Number Swaminathan Ramasubramanian http://orcid.org/0000-0001-8845-8427 Sangeetha Balaji http://orcid.org/0000-0002-1566-1333 Tejashri Kannan http://orcid.org/0009-0009-6400-5488 Naveen Jeyaraman http://orcid.org/0000-0002-4362-3326 Shilpa Sharma http://orcid.org/0000-0001-8695-8372 Filippo Migliorini http://orcid.org/0000-0001-7220-1221 Madhan Jeyaraman http://orcid.org/0000-0002-9045-9493
Funding Agency and Grant Number
Corresponding Author	Madhan Jeyaraman, MS, PhD, Assistant Professor, Research Associate, Department of Orthopaedics, ACS Medical College and Hospital, Dr MGR Educational and Research Institute, Velappanchavadi, Chennai 600077, Tamil Nadu, India. madhanjeyaraman@gmail.com
Key Words	Dosage calculation; Artificial intelligence; ChatGPT; Drug dosage; Healthcare; Large language models
Core Tip	This study reveals ChatGPT 4's superior accuracy in providing medical drug dosage information, highlighting the potential of artificial intelligence (AI) to aid healthcare professionals in minimizing medication errors. The analysis, based on Harrison's Principles of Internal Medicine, underscores the need for ongoing AI development to ensure reliability in critical medical situations. Variations in disease-specific and organ system accuracies suggest areas for improvement and continuous refinement of AI systems in medicine.
Publish Date	2024-07-26 08:29
Citation	<p>Ramasubramanian S, Balaji S, Kannan T, Jeyaraman N, Sharma S, Migliorini F, Balasubramaniam S, Jeyaraman M. Comparative evaluation of artificial intelligence systems' accuracy in providing medical drug dosages: A methodological study. <i>World J Methodol</i> 2024; 14(4): 92802</p>
URL	https://www.wjgnet.com/2222-0682/full/v14/i4/92802.htm
DOI	https://dx.doi.org/10.5662/wjm.v14.i4.92802

Full Article (PDF)	WJM-14-92802-with-cover.pdf
STROBE Statement	92802-STROBE-statement.pdf
Manuscript File	92802-Review-Filipodia.docx
Answering Reviewers	92802-answering-reviewers.pdf
Audio Core Tip	92802-audio.opus
Biostatistics Review Certificate	92802-biostatistics-statement.pdf
Conflict-of-Interest Disclosure Form	92802-conflict-of-interest-statement.pdf
Copyright License Agreement	92802-copyright-assignment.pdf
Signed Informed Consent Form(s) or Document(s)	92802-informed-consent-statement.pdf
Institutional Review Board Approval Form or Document	92802-institutional-review-board-statement.pdf
Non-Native Speakers of English Editing Certificate	92802-non-native-speakers.pdf
Supplementary Material	92802-supplementary-material.xlsx
Peer-review Report	92802-peer-reviews.pdf
Scientific Misconduct Check	92802-scientific-misconduct-check.png
Scientific Editor Work List	92802-scientific-editor-work-list.pdf
CrossCheck Report	92802-crosscheck-report.pdf