Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: An approach is proposed to discover diagnostic rules from clinical databases. First, the diseases in the clinical database are clustered by their necessary characterization. Then focusing mechanism, which includes three processes: exclusion process, discrimination process and combining process, is exploited to derive diagnostic rules. The main characteristic feature of the approach is: 1) coverage is exploited to find necessary characterization of diseases during the exclusion process, while accuracy is exploited to find lambda A -sufficient characterization of diseases during the discrimination process; 2) discrimination process can be executed among many diseases; 3) a series of classification information systems (CISs) derived by exclusion process from the original are considered; 4) the CISs are reducted to the simple ones; 5) crisp rules and uncertain rules can be conveniently derived. Finally, an example illustrates the approach and shows its effectiveness.
['Minghui Shi', 'Changle Zhou']
I am writing a research paper on a idea Diagnostic Rules Discovery with Hierarchical Clustering and Focusing Mechanism Based on Rough Sets Theory
[{"from": "human", "value": "I am writing a research paper on a idea Diagnostic Rules Discovery with Hierarchical Clustering and Focusing Mechanism Based on Rough Sets Theory"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: An approach is proposed to discover diagnostic rules from clinical databases. First, the diseases in the clinical database are clustered by their necessary characterization. Then focusing mechanism, which includes three processes: exclusion process, discrimination process and combining process, is exploited to derive diagnostic rules. The main characteristic feature of the approach is: 1) coverage is exploited to find necessary characterization of diseases during the exclusion process, while accuracy is exploited to find lambda A -sufficient characterization of diseases during the discrimination process; 2) discrimination process can be executed among many diseases; 3) a series of classification information systems (CISs) derived by exclusion process from the original are considered; 4) the CISs are reducted to the simple ones; 5) crisp rules and uncertain rules can be conveniently derived. Finally, an example illustrates the approach and shows its effectiveness."}]