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Volume 13
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10.3390/technologies13040142
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Article

Leveraging Artificial Intelligence for Personalized Rehabilitation Programs for Head and Neck Surgery Patients

by
Gianluca Marcaccini
1,2,
Ishith Seth
1,3,4,*,
Jennifer Novo
5,
Vicki McClure
1,
Brett Sacks
1,
Kaiyang Lim
1,
Sally Kiu-Huen Ng
4,
Roberto Cuomo
2 and
Warren M. Rozen
1,3
1
Department of Plastic and Reconstructive Surgery, Peninsula Health, Frankston, VIC 3199, Australia
2
Department of Plastic and Reconstructive Surgery, University of Siena, 53100 Siena, Italy
3
Faculty of Medicine and Surgery, Central Clinical School, Monash University, Clayton, VIC 3004, Australia
4
Department of Plastic and Reconstructive Surgery, Austin Health, Heidelberg, VIC 3084, Australia
5
Faculty of Medicine and Surgery, The University of Notre Dame, Sydney, NSW 2008, Australia
*
Author to whom correspondence should be addressed.
Technologies 2025, 13(4), 142; https://doi.org/10.3390/technologies13040142
Submission received: 17 February 2025 / Revised: 24 March 2025 / Accepted: 2 April 2025 / Published: 4 April 2025
(This article belongs to the Special Issue Assistive Technologies in Care and Rehabilitation: Research, Developments, and International Initiatives)
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Abstract

Background: Artificial intelligence (AI) and large language models (LLMs) are increasingly used in healthcare, with applications in clinical decision-making and workflow optimization. In head and neck surgery, postoperative rehabilitation is a complex, multidisciplinary process requiring personalized care. This study evaluates the feasibility of using LLMs to generate tailored rehabilitation programs for patients undergoing major head and neck surgical procedures. Methods: Ten hypothetical head and neck surgical clinical scenarios were developed, representing oncologic resections with complex reconstructions. Four LLMs, ChatGPT-4o, DeepSeek V3, Gemini 2, and Copilot, were prompted with identical queries to generate rehabilitation plans. Three senior clinicians independently assessed their quality, accuracy, and clinical relevance using a five-point Likert scale. Readability and quality metrics, including the DISCERN score, Flesch Reading Ease, Flesch–Kincaid Grade Level, and Coleman–Liau Index, were applied. Results: ChatGPT-4o achieved the highest clinical relevance (Likert mean of 4.90 ± 0.32), followed by DeepSeek V3 (4.00 ± 0.82) and Gemini 2 (3.90 ± 0.74), while Copilot underperformed (2.70 ± 0.82). Gemini 2 produced the most readable content. A statistical analysis confirmed significant differences across the models (p < 0.001). Conclusions: LLMs can generate rehabilitation programs with varying quality and readability. ChatGPT-4o produced the most clinically relevant plans, while Gemini 2 generated more readable content. AI-generated rehabilitation plans may complement existing protocols, but further clinical validation is necessary to assess their impact on patient outcomes.
Keywords: artificial intelligence; large language models; head and neck surgery; postoperative care; ChatGPT; DeepSeek artificial intelligence; large language models; head and neck surgery; postoperative care; ChatGPT; DeepSeek
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MDPI and ACS Style

Marcaccini, G.; Seth, I.; Novo, J.; McClure, V.; Sacks, B.; Lim, K.; Ng, S.K.-H.; Cuomo, R.; Rozen, W.M. Leveraging Artificial Intelligence for Personalized Rehabilitation Programs for Head and Neck Surgery Patients. Technologies 2025, 13, 142. https://doi.org/10.3390/technologies13040142

AMA Style

Marcaccini G, Seth I, Novo J, McClure V, Sacks B, Lim K, Ng SK-H, Cuomo R, Rozen WM. Leveraging Artificial Intelligence for Personalized Rehabilitation Programs for Head and Neck Surgery Patients. Technologies. 2025; 13(4):142. https://doi.org/10.3390/technologies13040142

Chicago/Turabian Style

Marcaccini, Gianluca, Ishith Seth, Jennifer Novo, Vicki McClure, Brett Sacks, Kaiyang Lim, Sally Kiu-Huen Ng, Roberto Cuomo, and Warren M. Rozen. 2025. "Leveraging Artificial Intelligence for Personalized Rehabilitation Programs for Head and Neck Surgery Patients" Technologies 13, no. 4: 142. https://doi.org/10.3390/technologies13040142

APA Style

Marcaccini, G., Seth, I., Novo, J., McClure, V., Sacks, B., Lim, K., Ng, S. K.-H., Cuomo, R., & Rozen, W. M. (2025). Leveraging Artificial Intelligence for Personalized Rehabilitation Programs for Head and Neck Surgery Patients. Technologies, 13(4), 142. https://doi.org/10.3390/technologies13040142

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