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Artificial Intelligence in Supportive Oncology and Symptom Management Opportunities
Elyssa N Kim1,2, Krisstina Gowin1, Anne Reb1
1City of Hope National Medical Center, Los Angeles, CA.
Artificial intelligence (AI) enhances oncology supportive care by personalizing symptom management and predicting adverse events. This technology promises improved patient outcomes and quality of life, despite implementation challenges.
Area of Science:
- Oncology
- Medical Informatics
- Artificial Intelligence
Background:
- Artificial intelligence (AI) is increasingly integrated into healthcare, offering novel approaches to patient care.
- Supportive care and symptom management are crucial components of oncology treatment.
- Personalized interventions are needed to improve patient-reported outcomes in cancer care.
Purpose of the Study:
- To review current research on AI applications in oncology supportive care.
- To explore AI's potential for personalizing interventions and managing symptoms.
- To identify challenges and future directions for AI in supportive oncology.
Main Methods:
- Literature review synthesizing current research on AI in oncology supportive care.
- Examination of AI-driven tools for symptom monitoring and adverse event prediction.
- Analysis of machine learning integration for real-time data and personalized recommendations.
Main Results:
- AI offers personalized symptom monitoring and predictive analytics for adverse events.
- Machine learning enables real-time data analysis for proactive interventions and symptom relief.
- AI applications show potential for improving patient-reported outcomes in supportive oncology.
Conclusions:
- AI integration in supportive oncology can personalize care and optimize symptom control.
- AI has the potential to significantly improve the quality of life for cancer patients.
- Challenges such as data privacy, bias, and validation need to be addressed for widespread clinical adoption.
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