Aim

This study aims to investigate the role and potential of artificial intelligence (AI) applications in oncological rehabilitation. In particular, it examines how data analytics and predictive models can be used and how these technologies can improve patient monitoring. The contributions of AI to increasing the effectiveness of treatment, reducing its side effects and improving its results will be discussed.

Method

This study was carried out in two stages: literature review and case studies. Academic studies published in the last decade (2014-2024) were examined using the PubMed, IEEE Xplore and Scopus databases. Additionally, performance metrics have been used to measure the effectiveness of AI-based applications. Application examples are supported by case studies from various institutions.

Results

The use of AI in oncological rehabilitation has been examined under three main headings: data analytics, prediction models and application examples.

1. Data Analytics: AI plays a critical role in analyzing large data sets. Oncology rehabilitation data includes patients' response to treatment, treatment-related side effects, and general health status. By analyzing this data, machine learning algorithms have the potential to optimize patients' personalized treatment plans.

2. Predictive Models: AI is used to predict the future health status of patients. Neural networks and regression models can predict complications after cancer treatment. These models guide healthcare professionals in taking proactive precautions.

3. Application Examples: Case studies show that AI-based rehabilitation programs have the potential to improve patients' quality of life. In some studies, AI has identified cancer subtypes and determined the most appropriate treatment methods. AI-supported mobile robotic exoskeletons have been found effective in motor rehabilitation.

Conclusion

Research shows that AI applications have the potential to improve patient care in oncology rehabilitation. Data analytics and predictive models have the capacity to make treatment processes more effective and individualized. However, the current knowledge about ethics and safety of the applications of AI in healthcare is insufficient. In the future, it is expected that AI will be used more widely in oncological rehabilitation with further research and development studies.