DengueFog: A Fog Computing-Enabled Weighted Random Forest-Based Smart Health Monitoring System for Automatic Dengue Prediction.

Dengue is a distinctive and fatal infectious disease that spreads through female mosquitoes called Aedes aegypti. It is a notable concern for developing countries due to its low diagnosis rate. Dengue has the most astounding mortality level as compared to other diseases due to tremendous platelet depletion.

Cloud-Based Advanced Shuffled Frog Leaping Algorithm for Tasks Scheduling.

In recent years, the world has seen incremental growth in online activities owing to which the volume of data in cloud servers has also been increasing exponentially. With rapidly increasing data, load on cloud servers has increased in the cloud computing environment. With rapidly evolving technology, various cloud-based systems were developed to enhance the user experience.

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.

Seminal quality prediction using data mining methods.

Background: Now-a-days, some new classes of diseases have come into existences which are known as lifestyle diseases. The main reasons behind these diseases are changes in the lifestyle of people such as alcohol drinking, smoking, food habits etc. After going through the various lifestyle diseases, it has been found that the fertility rates (sperm quantity) in men has considerably been decreasing in last two decades.

Prediction of different types of liver diseases using rule based classification model.

Background: Diagnosing different types of liver diseases clinically is a quite hectic process because patients have to undergo large numbers of independent laboratory tests. On the basis of results and analysis of laboratory test, different liver diseases are classified. Hence to simplify this complex process, we have developed a Rule Base Classification Model (RBCM) to predict different types of liver diseases.

Predication of Parkinson's disease using data mining methods: a comparative analysis of tree, statistical, and support vector machine classifiers.

The prediction of Parkinson's disease in early age has been challenging task among researchers, because the symptoms of disease came into existence in middle and late middle age. There are lots of symptoms that lead to Parkinson's disease. But this article focuses on the speech articulation difficulty symptoms of PD affected people and try to formulate the model on the behalf of three data mining methods.