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The Colorectal Cancer Recurrence Support (CARES) System
L S Ong1, B Shepherd, L C Tong
1Institute of Systems Science, National University of Singapore, Singapore. leansuan@iss.nus.sg
Artificial Intelligence in Medicine
|December 31, 1997
Summary
This study introduces the Cancer Recurrence Support (CARES) System to predict colorectal cancer recurrence after surgery. Early detection via CARES aims to improve patient survival rates.
Area of Science:
- Oncology
- Medical Informatics
- Artificial Intelligence
Background:
- Colorectal cancer is Singapore's second most common cancer.
- Post-surgery recurrence affects up to 50% of patients.
- Early recurrence detection is crucial for treatment efficacy and survival.
Purpose of the Study:
- To introduce the Cancer Recurrence Support (CARES) System.
- To predict colorectal cancer recurrence using Case-based Reasoning (CBR).
- To identify high-risk patient groups for proactive management.
Main Methods:
- Utilizing Case-based Reasoning (CBR) for patient case comparison.
- Integrating data mining and natural language processing techniques.
- Developing a system to infer recurrence risk based on historical and new patient data.
Main Results:
- The CARES System facilitates comparison of new and past patient cases.
- Inferences are drawn to identify patient groups at high risk of recurrence.
- The system's features and functionality for recurrence prediction are detailed.
Conclusions:
- The CARES System offers a novel approach to predicting colorectal cancer recurrence.
- Early identification of at-risk patients can be enhanced.
- This system supports improved therapeutic strategies and patient outcomes.