By Hiroyuki Yoshida, Ashlesha Jain, Ajita Ichalkaranje, Nikhil Ichalkaranje
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Extra resources for Advanced Computational Intelligence Paradigms in Healthcare-2
Johnson3 , and Herbert S. org As healthcare costs continue to spiral upward, healthcare institutions are under enormous pressure to create cost eﬃcient systems without risking quality of care. Healthcare IT applications provide considerable promises for achieving this multifaceted goal through managing inofrmation, reducing costs, and facilitating total quality management and continuous quality improvement programs. However, the desired outcome can not be achieved if these applications are not being used.
The system 3 Application of Artiﬁcial Intelligence for Weekly Dietary Menu Planning 31 is also capable of storing and organizing patients’ dietary records and other health-diet related information, which allows dietetians to eﬀectively evaluate and monitor the patients’ dietary changes throughout the period of consultations. While more than a few expert systems have been developed recently for nutrition counseling, a solution that at least tries to satisfy each and every aspect of an ideal menu planning is still missing.
7 shows, the 103 occurrences are shared somewhat proportional among the other alleles (“A” is 15th , “B” is the 12th allele in Fig. 7). We performed single sample Lilliefors hypothesis test of composite normality on the samples with an element size of 10 on 100 runs of the algorithm with 10 diﬀerent starting populations and counting the occurrences of “A” and “B”. The distribution of the occurrences of “A” in function of the starting populations proved normal, except for one case. 3. Statistical analysis of the distribution of the potential alleles (drinks) in the best solutions (lunches) and the mean occurrence of the alleles (A,B) on which the rules were imposed 44 B.