Role of Soft Computing Approaches in HealthCare Domain: A Mini Review.

In the present era, soft computing approaches play a vital role in solving the different kinds of problems and provide promising solutions. Due to popularity of soft computing approaches, these approaches have also been applied in healthcare data for effectively diagnosing the diseases and obtaining better results in comparison to traditional approaches. Soft computing approaches have the ability to adapt itself according to problem domain. Another aspect is a good balance between exploration and exploitation processes. These aspects make soft computing approaches more powerful, reliable and efficient. The above mentioned characteristics make the soft computing approaches more suitable and competent for health care data. The first objective of this review paper is to identify the various soft computing approaches which are used for diagnosing and predicting the diseases. Second objective is to identify various diseases for which these approaches are applied. Third objective is to categories the soft computing approaches for clinical support system. In literature, it is found that large number of soft computing approaches have been applied for effectively diagnosing and predicting the diseases from healthcare data. Some of these are particle swarm optimization, genetic algorithm, artificial neural network, support vector machine etc. A detailed discussion on these approaches are presented in literature section. This work summarizes various soft computing approaches used in healthcare domain in last one decade. These approaches are categorized in five different categories based on the methodology, these are classification model based system, expert system, fuzzy and neuro fuzzy system, rule based system and case based system. Lot of techniques are discussed in above mentioned categories and all discussed techniques are summarized in the form of tables also. This work also focuses on accuracy rate of soft computing technique and tabular information is provided for each category including author details, technique, disease and utility/accuracy.

Impact of a workplace intervention on attitudes and practices related to gender equity in Bengaluru, India.

We describe the evaluation of a participatory, garment factory-based intervention to promote gender equity. The intervention comprised four campaigns focused on gender and violence against women, alcoholism, sexual and reproductive health, and HIV/AIDS, which were implemented using information displays (standees and posters) and interactive methods (street play, one-to-one interactions, experience-sharing, and health camps). Each campaign lasted six days and the entire intervention was implemented over 10 months. We evaluated the intervention using a quasi-experimental design in which one factory served as the intervention site and a second as a delayed control. Two mobile-phone-based cross-sectional surveys were conducted at baseline and 12 months with separate systematic random samples of employees from each site. Data on socio-demographic characteristics and knowledge and attitudes related to gender equity, intimate partner violence (IPV) and alcohol use were assessed, and differences in these variables associated with the intervention were examined using difference-in-difference estimation. Analyses of data from 835 respondents revealed substantial, statistically significant improvements in attitudes related to gender equity, unacceptability of IPV, and awareness of IPV and alcohol-related support services. In conclusion, our study offers compelling evidence on the effectiveness of workplace-based interventions in advancing gender equity.