Machine Learning una solución para mejorar la percepción del dolor en pacientes de dolor oncológico al predecir y mejorar la gestión de este síntoma en la práctica médica actual

Rueda Aldana, Laura Sofia

Machine Learning una solución para mejorar la percepción del dolor en pacientes de dolor oncológico al predecir y mejorar la gestión de este síntoma en la práctica médica actual

Abstract

Introduction: With the increasing prevalence of cancer worldwide, interest has increased in the control of complications and symptoms derived from this pathology, especially cancer pain, which is the most common symptom experienced by these patients and, taking into account that cancer pain is a chronic condition, with mixed and multifactorial characteristics, which makes this symptom very complex to manage, since it requires a multidisciplinary approach for its treatment, as well as the use of analgesia that goes beyond the standardized analgesic strategies, which is costly for health systems worldwide, the need arises to find innovative and cost-effective tools that can help improve the approach to this symptom effectively. Due to the above, it is considered that the answer to this problem could lie in the use and development of machine learning tools. Objective: The present systematic review aims to determine if it is possible, through machine learning tools, to optimize the management of the perception of oncological pain and predict the response to pain treatment in patients with cancer, susceptible to being used in current clinical practice. Methodology: A review of the literature was carried out in the PubMed and Cochrane databases between the months of March and April 2024 and the CASPe critical reading criteria were applied for the selection of the articles. Results: A total of 21 articles were obtained, one of which was a systematic review, finding that in the last 6 years these machine learning tools have been explored for the management of oncological pain, their main uses being the identification of predictors or risk factors that determine the appearance of cancer pain and the prediction of pain treatment requirements or its exacerbations. Conclusions: Thanks to this review of the literature, it was observed that machine learning in the field of cancer pain management is incipient, but with great potential for the development of useful tools to make diagnosis, follow-up and more efficient treatment of this condition in cancer patients.

Citation

Rueda Aldana, L. (2024). Machine Learning una solución para mejorar la percepción del dolor en pacientes de dolor oncológico al predecir y mejorar la gestión de este síntoma en la práctica médica actual. Universitat Oberta de Catalunya (UOC). https://hdl.handle.net/10609/150965

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