Predicting Asthma-Related Emergency Department Visits Using Big Data - 2015


Asthma is one in all the foremost prevalent and costly chronic conditions within the United States, which can't be cured. However, accurate and timely surveillance data might permit for timely and targeted interventions at the community or individual level. Current national asthma disease surveillance systems will have knowledge availability lags of up to 2 weeks. Rapid progress has been created in gathering nontraditional, digital info to perform disease surveillance. We tend to introduce a unique methodology of using multiple information sources for predicting the amount of asthma-related emergency department (ED) visits in a specific area. Twitter data, Google search interests, and environmental sensor data were collected for this purpose. Our preliminary findings show that our model will predict the quantity of asthma ED visits based on close to-real-time environmental and social media data with approximately seventy% precision. The results will be helpful for public health surveillance, ED preparedness, and targeted patient interventions.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE :A Machine Learning Approach for Tracking and Predicting Student Performance in Degree Programs - 2018ABSTRACT:Accurately predicting students' future performance based on their ongoing academic records is crucial
PROJECT TITLE : Predicting Social Emotions from ReadersÕ Perspective - 2017 ABSTRACT: Thanks to the speedy development of Net, massive numbers of documents assigned by readers’ emotions have been generated
PROJECT TITLE : Predicting Persuasive Message for Changing StudentÕs Attitude using Data Mining - 2017 ABSTRACT: This paper aims to predict the factors and build prediction models for the persuasive message changing
PROJECT TITLE : Low-Power ECG-Based Processor for Predicting Ventricular Arrhythmia - 2016 ABSTRACT: This paper presents the look of a absolutely integrated electrocardiogram (ECG) signal processor (ESP) for the prediction
PROJECT TITLE :Predicting Cross-Core Performance Interference on Multicore Processors with Regression AnalysisABSTRACT:Despite their widespread adoption in cloud computing, multicore processors are heavily underneath-utilized

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry