Treatment decisions in axillary node-negative breast cancer patients.

摘要: Treatment decisions must be made on 9000 axillary node-negative breast cancer patients each month in the United States. Which of these will benefit from adjuvant therapy is a major question. Valid methods are needed to distinguish those who "cured" suffer recurrence. A complex network prognostic variables enters into treatment decision, together with risk-versus-benefit assessment. We using neural-network-based form artificial intelligence that, once "trained" data representing an event and its outcome, can identify subsets low recurrence risks. Larger sets being evaluated hope introducing neural-network technique routine clinical practice.