Research papers on data mining in healthcare


research papers on data mining in healthcare

satisfaction and corporate profits. We were surprised by what we found; fundamentally, were using the fact that the electronic health record has a lot of diseases and phenotypes tracked in it, and we can mine those and assess them in a rapid way. You can look for clusters of diseases that could be organized by a gene, says Denny, who notes that examining outcomes in EHRs can be valuable in deciding if a genetic variant might be associated with a disease. Data mining allows to find a segment of customers based on vulnerability and the business could offer them with special offers and enhance satisfaction. In the clinical world, I would love to try to turn this into something thats more like decision support. Science, suggest that patients diagnosed with heart failure, stroke, infertility and kidney failure could actually be suffering from rare and undiagnosed genetic diseases.

research papers on data mining in healthcare

Rajiv Sambasivan, in Press, Corrected Proof, Available online Purchase PDF, research articleAbstract only, towards Sustainable Smart City by Particulate Matter Prediction Using Urban Big Data, Excluding Expensive Air Pollution Infrastructures. Data mining also helps extract data which is more relevant to the problem. Applications of data mining to bioinformatics include gene finding, protein function inference, disease diagnosis, the short essay let grow your own food disease prognosis, disease treatment optimization, protein and gene interaction network reconstruction, data cleansing, and protein sub-cellular location prediction. It helps an analyst to distinguish an activity from common everyday network activity. Agent-based Data Analysis and Knowledge Discovery. IT Software Development and Methodology, data Mining for Biological and Environmental Problems. Law enforcement can use mining techniques to investigate crimes, monitor communication of suspected terrorists. Data mining can also help healthcare insurers to detect fraud and abuse. Prediction Systems, decision Analysis and Decision Support Systems.

Today, we are pioneering the most promising and disruptive technologies that will transform industries and society, including the future of AI, blockchain and quantum computing. We are driven to discover. Reddy is an associate professor in the Department of Computer Science at Wayne State University. He received his PhD from Cornell University and MS from Michigan State University.

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