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Collective intelligence has drawn many scientists’ attention in many centuries. This paper shows the collective intelligence study process in a perspective of crowd science.

After summarizing the time-order process of related researches, different points of views on collective intelligence’s measurement and their modeling methods were outlined.

The authors show the recent research focusing on collective intelligence optimization. The studies on application of collective intelligence and its future potential are also discussed.

This paper will help researchers in crowd science have a better picture of this highly related frontier interdiscipline.

Breast cancer is an important medical disorder, which is not a single disease but a cluster more than 200 different serious medical complications.

The new artificial bee colony (ABC) implementation has been applied to probabilistic neural network (PNN) for training and testing purpose to classify the breast cancer data set.

The new ABC algorithm along with PNN has been successfully applied to breast cancers data set for prediction purpose with minimum iteration consuming.

The new implementation of ABC along PNN can be easily applied to times series problems for accurate prediction or classification.