Clinical Decision Support System for Diabetes Based on Ontology Reasoning and TOPSIS Analysis

Table 11

Survey of “Patient-Centered Treatment Decision Support System for Diabetes Based on Fuzzy Logic and Domain Ontology”.

Question	Scoring
	1	2	3	4	5
What do you think about “Patient ideal HbA1c target inference”?; Are you satisfied with its accuracy?
Is the “Method 1: Safety fuzzy rules” accurate?	□	□	□	□	□
Are you satisfied with the results of the “Method 1: Safety fuzzy rules”?	□	□	□	□	□
Is the “Method 2: Positivity fuzzy rules” accurate?	□	□	□	□	□
Are you satisfied with the results of the “Method 2: Positivity fuzzy rules”?	□	□	□	□	□
What do you think about “Antidiabetic medications reasoning and ranking”?; Are you satisfied with its accuracy?
Is the “Antidiabetic medications reasoning and ranking” accurate?	□	□	□	□	□
Are you satisfied with the results of the “Antidiabetic medications reasoning and ranking”?	□	□	□	□	□
Do you think the system can provide some benefits for you?
Using the system improves my performance in my job.	□	□	□	□	□
Using the system enhances my effectiveness in my job.	□	□	□	□	□
I find the system to be useful in my job.	□	□	□	□	□
If this system used in conjunction with the actual work, would you continue to use this system at work?
I enjoy using this system at work.	□	□	□	□	□
I will frequently use this system in the future.	□	□	□	□	□
I will strongly recommend to others to use this system.	□	□	□	□	□

Title: ○Endocrinologists ○Attending physicians ○Resident physicians
Gender: ○Male ○Female
E-mail: