Essential roles for receiver operating characteristic (ROC) methodology in classifier neural network applications

Proceedings of the International Joint Conference on Neural Networks

Volumn 4, Issue , 2001, Pages 2730-2731

  DeLeo, J M ^a   Rosenfeld, S J ^a  

^a NATIONAL INSTITUTES OF HEALTH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER AIDED DIAGNOSIS; DECISION MAKING; OPTIMIZATION; PATIENT TREATMENT; PREDICTIVE CONTROL SYSTEMS;

CLASSIFIER NEURAL NETWORK APPLICATIONS; PATIENT MANAGEMENT; RECEIVER OPERATING CHARACTERISTIC;

NEURAL NETWORKS;

EID: 0034877720     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. Decision making studies in patient management
2. Signal delectability and medical decision-making
3. Editorial: ROC recollected
4. The fuzzy receiver operating characteristic function and medical decisions with uncertainty
5. Receiver Operating Characteristic Laboratory (ROCLAB); software for developing decision strategies that account for uncertainty
6. Receiver operating characteristic function as a tool for uncertainty management in artificial neural network decision-making
7. Receiver Operating Characteristic (ROC) curves: A fundamental tool in clinical medicine
8. Prospective validation of an acute respiratory distress syndrome predictive score
9. Prevalence-value-accuracy plots: A new method for comparing diagnostic tests based on misclassification costs
10. 'Smart computing' in the clinical laboratory
11. Machine-learned medical outcome indexes
12. Artificial neural networks: Opening the black box
13. Medical applications of neural networks: Measures of certainty and statistical tradeoffs
14. Statistical considerations in classifier systems