Book ChapterDOI
Clustering Algorithms for Big Data: A Survey
Prasanta K. Jana
- pp 155-174
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The article was published on 2016-10-26. It has received 31 citations till now. The article focuses on the topics: Cluster analysis & Big data.read more
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Journal ArticleDOI
A new architecture of Internet of Things and big data ecosystem for secured smart healthcare monitoring and alerting system
Gunasekaran Manogaran,R. Varatharajan,Daphne Lopez,Priyan Malarvizhi Kumar,Revathi Sundarasekar,Chandu Thota +5 more
TL;DR: A new architecture for the implementation of IoT to store and process scalable sensor data (big data) for health care applications and uses MapReduce based prediction model to predict the heart diseases is proposed.
Journal ArticleDOI
Wearable sensor devices for early detection of Alzheimer disease using dynamic time warping algorithm
TL;DR: This paper uses dynamic time warping (DTW) algorithm to compare the various shapes of foot movements collected from the wearable IoT devices to evaluate the effectiveness of the DTW method for Alzheimer disease diagnosis.
Journal ArticleDOI
Hybrid Recommendation System for Heart Disease Diagnosis based on Multiple Kernel Learning with Adaptive Neuro-Fuzzy Inference System
TL;DR: The proposed MKL with ANFIS based deep learning method follows two-fold approach and has produced high sensitivity, high specificity and less Mean Square Error for the for the KEGG Metabolic Reaction Network dataset.
Journal ArticleDOI
Machine Learning Based Big Data Processing Framework for Cancer Diagnosis Using Hidden Markov Model and GM Clustering
Gunasekaran Manogaran,V. Vijayakumar,R. Varatharajan,Priyan Malarvizhi Kumar,Revathi Sundarasekar,Ching-Hsien Hsu +5 more
TL;DR: A Bayesian hidden Markov model (HMM) with Gaussian Mixture (GM) Clustering approach is used to model the DNA copy number change across the genome and is compared with various existing approaches such as Pruned Exact Linear Time method, binary segmentation method and segment neighborhood method.
Journal ArticleDOI
A big data classification approach using LDA with an enhanced SVM method for ECG signals in cloud computing
TL;DR: SVM model with a weighted kernel function method is significantly identifies the Q wave, R wave and S wave in the input ECG signal to classify the heartbeat level to prove the effectiveness of the proposed Linear Discriminant Analysis (LDA) with an enhanced kernel based Support Vector Machine (SVM) method.
References
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Journal ArticleDOI
MapReduce: simplified data processing on large clusters
Jeffrey Dean,Sanjay Ghemawat +1 more
TL;DR: This paper presents the implementation of MapReduce, a programming model and an associated implementation for processing and generating large data sets that runs on a large cluster of commodity machines and is highly scalable.
Journal ArticleDOI
MapReduce: simplified data processing on large clusters
Jeffrey Dean,Sanjay Ghemawat +1 more
TL;DR: This presentation explains how the underlying runtime system automatically parallelizes the computation across large-scale clusters of machines, handles machine failures, and schedules inter-machine communication to make efficient use of the network and disks.
Journal ArticleDOI
Big Data In Health Care: Using Analytics To Identify And Manage High-Risk And High-Cost Patients
TL;DR: Six use cases are presented where some of the clearest opportunities exist to reduce costs through the use of big data: high-cost patients, readmissions, triage, decompensation, adverse events, and treatment optimization for diseases affecting multiple organ systems.
Journal ArticleDOI
Mining big data: current status, and forecast to the future
Wei Fan,Albert Bifet +1 more
TL;DR: This issue introduces four articles, written by influential scientists in the field, covering the most interesting and state-of-the-art topics on Big Data mining, and presents a broad overview of the topic, its current status, controversy, and a forecast to the future.
Journal ArticleDOI
Big data: The future of biocuration.
Doug Howe,Maria C. Costanzo,Petra Fey,Takashi Gojobori,Linda Hannick,Winston Hide,Winston Hide,David P. Hill,Renate Kania,Mary L. Schaeffer,Mary L. Schaeffer,Susan E. St. Pierre,Simon N. Twigger,Owen White,Seung Y. Rhee +14 more
TL;DR: To thrive, the field that links biologists and their data urgently needs structure, recognition and support.