Mental disorders and addictive behaviors, such as anxiety disorder, depression disorder, bipolar disorder, drug and alcohol addiction, and Internet addiction, have affected nearly 450 million people worldwide and around 20% of world’s children and adolescents are suffering from mental disorders as stated by WHO (World Health Organization). Research for helping psychiatrists to construct a good health care system has been just started. Among different clinical interventions for the mental disorders and addictive behaviors, group therapy is considered as a very effective clinical treatment. However, finding an effective therapy group for helping the patients is very challenging since some crucial criteria should be carefully considered simultaneously. Manual selection of therapy group members, which is the common approach for most psychiatrists and mental health professionals today, may incur human bias and is very time-consuming. Moreover, some of the researchers start to use machine learning and data mining method to predict the mental disease by mining the social network data. Recently mining social network data of individuals, is treated as a complementary alternative to the conventional psychological approach, which provides an excellent opportunity to actively identify those mental disorders at an early stage.
In this talk I will talk about the related works correlated with the health care system that first helping psychiatrists to form an effective therapy group to treat the patient, and second trying to maintain the therapy group effectiveness while doing the treatment, and the last trying to find the abnormal behaviors of the patients at an early stage. I will briefly talk about what people are doing right now and give some of the thought about it and the new problems I can work with.