Precision Medicine in Physical and Rehabilitation Medicine (PRM)

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DOI:

https://doi.org/10.25759/spmfr.577

Palavras-chave:

Precision Rehabilitation, Physical and Rehabilitation Medicine, Big Data, Artificial Intelligence, Biomarkers, Genetics, Neuroimaging, Biopsychosocial Approach

Resumo

Precision Rehabilitation (PR) represents a transformative approach in Physical and Rehabilitation Medicine (PRM), emphasizing the integration of personalized care with the best clinical evidence to enhance patient outcomes. This article discusses the pivotal role of emerging technologies such as Big Data (BD) and Artificial Intelligence (AI) in revolutionizing rehabilitation practices. By leveraging vast datasets and advanced algorithms, healthcare professionals can develop tailored therapeutic plans, optimize interventions, and monitor patient progress in real-time. Additionally, the integration of genetic insights and biomarkers into rehabilitation programs allows for a more nuanced understanding of individual patient responses, facilitating personalized treatment strategies. Neuroimaging techniques further enhance the predictive capabilities regarding functional recovery, while psychosocial and environmental factors are acknowledged as critical components in formulating comprehensive rehabilitation plans. Despite the promising advancements, challenges such as ethical considerations, data privacy, and the need for standardized protocols remain. This article underscores the importance of a biopsychosocial approach in rehabilitation, advocating for a patient-centered model that adapts to the unique characteristics and needs of each individual. As PR continues to evolve, it holds the potential to redefine rehabilitation care, making personalized medicine a practical reality in clinical settings.

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Publicado

2025-12-24

Como Citar

1.
Pinheiro J, Branco J, Aguiar-Branco C, Laíns J, Zão A, Nunes R, et al. Precision Medicine in Physical and Rehabilitation Medicine (PRM). SPMFR [Internet]. 24 de Dezembro de 2025 [citado 17 de Janeiro de 2026];37(3):12-7. Disponível em: https://spmfrjournal.org/index.php/spmfr/article/view/577

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Vol. 37 N.º 3 (2025): Ano 33

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