4 research outputs found
GP-ELM-RNN: Garson-pruned extreme learning machine based replicator neural network for anomaly detection
No full textBig Data Mining: Tools & Algorithms
No full textWe are now in Big Data era, and there is a growing demand for tools which can process and analyze it. Big data analytics deals with extracting valuable information from that complex data which can’t be handled by traditional data mining tools. This paper surveys the available tools which can handle large volumes of data as well as evolving data streams. The data mining tools and algorithms which can handle big data have also been summarized, and one of the tools has been used for mining of large datasets using distributed algorithms
A machine learning solution for bed occupancy issue for smart healthcare sector
No full textThe health care domain is a culmination and emergence of many other economic sectors that give different services from patient treatment to healing, protective, rehabilitation, and palliative care. The GDP consumes to facilitate health in terms of smart device development, clinical examinations, outsourcing, and tele-medication facilities. The Asian countries and less developed countries with a high population rate are facing health care services related issues. One of these countries is India. India has two types of health care services systems: (i) public service system and (ii) private system. The public health system, i.e., the government, provides facilities to patients as primary health centers (PHCs) through limited secondary and tertiary health institutions like hospitals in rural areas while the private service is owned by local practitioners and institutions. Both of these service providers are facing bed occupancy issues for patients due to a highly populated country. To overcome this issue, we propose a machine learning solution for patient admission scheduling autonomously. The proposed framework helps hospitals to enhance the decision process for bed occupancy for patients concerning their departments and their diseases. We have deployed our framework in real time environment and find that it facilitates the overall performance of bed allocation in the prescribed hospitals
