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Published

January 10, 2025

Title

Artificial Intelligence Tools for Scientific Writing: The Good, The Bad and The Ugly

Authors

Giuseppe Biondi-Zoccai, Anna Cazzaro, Elisa Cobalchin, Diletta D’Auria, Giovanni Ardizzone, Salvatore Giordano, Ulvi Mirzoyev, Petar M Seferovic, Gani Bajraktari, Denisa Muraru.

DOI

10.62684/BXVS8359

Keywords

Artificial Intelligence; ChatGPT; Medical writing; Peer review; Research; Science; Scientific writing.

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Giuseppe Biondi-Zoccai^(a,b), Anna Cazzaro^(a), Elisa Cobalchin^(a), Diletta D’Auria^(a), Giovanni Ardizzone^(a), Salvatore Giordano^(c), Ulvi Mirzoyev^(d), Petar M Seferovic^(e), Gani Bajraktari^(f,g,h), Denisa Muraru^(i,j)

^(a) Department of Medical-Surgical Sciences and Biotechnologies, Sapienza University of Rome, Latina, Italy. giuseppe.biondizoccai@uniroma1.it

^(b) Maria Cecilia Hospital, GVM Care & Research, Cotignola, Italy.

^(c) Division of Cardiology, Department of Medical and Surgical Sciences, "Magna Graecia" University, Catanzaro, Italy. sasigiordano@gmail.com

^(d) Medical Center of the Ministry of Emergency Situations, Baku, Azerbaijan. ulvi.mirzoyev@adam.az

^(e) Faculty of Medicine, University of Belgrade, Serbian Academy of Sciences and Arts, Belgrade, Serbia. seferovic.petar@gmail.com

^(f) Clinic of Rheumatology, University Clinical Centre of Kosova, Prishtina, Kosova. ganibajraktari@gmail.com

^(g) Clinic of Cardiology, University Clinical Centre of Kosova, Prishtina, Kosovo.

^(h) Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.

⁽ⁱ⁾ Department of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy. denisa.muraru@gmail.com

^(j) Department of Cardiology, Istituto Auxologico Italiano, IRCCS, Milan, Italy.

Correspondence to: Prof. Giuseppe Biondi-Zoccai, Department of Medical-Surgical Sciences and Biotechnologies, Sapienza University of Rome, Corso della Repubblica 74, 04100 Latina, Italy. Email: giuseppe.biondizoccai@uniroma1.it

Abstract

The integration of artificial intelligence (AI) tools in the workflow of scholarly writing, including scientific and medical writing, offers transformative advantages while raising critical ethical and practical concerns. Among the pros, AI substantially enhances efficiency by automating several time-consuming tasks such as literature review, data synthesis and text editing. In particular, tools such as ChatGPT, Grammarly, and SciSpace Copilot remarkably empower researchers when they draft, refine, and format manuscripts, increasing precision and speed. In addition, AI tools may foster inclusivity by assisting non-native English speakers with seamless translations and also enabling interdisciplinary collaboration, thereby hopefully democratizing access and boosting scientific communication and cooperation. However, the rapid adoption of novel AI tools brings significant challenges. First, there is a distinct risk of perpetuating biases in training datasets, and other key issues include ambiguity in authorship accountability and the potential erosion of critical thinking skills. In addition, AI tools could be purposefully misused to generate mock datasets and fraudulent papers (e.g. by paper mills), and this clearly poses a threat to academic integrity. This challenge is all too pressing given that traditional plagiarism detection tools often fall short against sophisticated AI-generated content. We hereby explore the pros and cons of AI on medical writing, poignantly leveraging Sergio Leone’s The Good, The Bad, and The Ugly movie as a metaphor. By providing general concepts as well as focusing on several key AI tools, we are hopeful this overview may prove useful to anyone wishing to conscientiously adopt AI tools for scientific writing. In addition, we make a compelling case for transparent guidelines, robust and freely available detection mechanisms, and ongoing critical oversight to ensure AI will be able to serve as a catalyst for innovation and dissemination without compromising the credibility of scholarly endeavors.

Declarations

Conflict of interest

Giuseppe Biondi-Zoccai has consulted for Abiomed, Advanced Nanotherapies, Aleph, Amarin, Balmed, Cardionovum, Crannmedical, Endocore Lab, Eukon, Guidotti, Innovheart, Meditrial, Menarini, Microport, Opsens Medical, Terumo, and Translumina, outside the present work. Denisa Muraru reports research support and speakers' fees from GE Healthcare and Philips Medical Systems, outside the present work. All other authors report no conflict of interest.

Acknowledgement

Research leading to this report has received funding from the European Union - NextGenerationEU, through the Italian Ministry of University and Research, under PNRR - M4C2-I1.3 Project PE_00000019 "HEAL ITALIA" to Giuseppe Biondi-Zoccai CUP B53C22004000006 Sapienza University of Rome. The views and opinions expressed are those of the authors only and do not necessarily reflect those of the European Union or the European Commission. Neither the European Union nor the European Commission can be held responsible for them. This manuscript was based on analysis conducted and was drafted with the assistance of artificial intelligence tools, including ChatGPT 4 (OpenAI, San Francisco, CA, USA), in keeping with established best practices (Biondi-Zoccai G, editor. ChatGPT for Medical Research. Torino: Edizioni Minerva Medica; 2024). The final content, including all conclusions and opinions, has been thoroughly revised, edited, and approved by the authors. The authors take full responsibility for the integrity and accuracy of the work and retain full credit for all intellectual contributions. Compliance with ethical standards and guidelines for the use of artificial intelligence in research has been ensured.