Personalized healthcare cloud services for disease risk assessment and wellness management using social media

[1]  Laurence T. Yang,et al.  A Cloud Based Framework for Identification of Influential Health Experts from Twitter , 2015, 2015 IEEE 12th Intl Conf on Ubiquitous Intelligence and Computing and 2015 IEEE 12th Intl Conf on Autonomic and Trusted Computing and 2015 IEEE 15th Intl Conf on Scalable Computing and Communications and Its Associated Workshops (UIC-ATC-ScalCom).

[2]  Jeanna Neefe Matthews,et al.  Fake Twitter accounts: profile characteristics obtained using an activity-based pattern detection approach , 2015, SMSociety.

[3]  S. Khan,et al.  A survey on context-aware recommender systems based on computational intelligence techniques , 2015, Computing.

[4]  Shein-Chung Chow,et al.  On Big-Data Analytics in Biomedical Research , 2015 .

[5]  John Yen,et al.  Finding influential users of online health communities: a new metric based on sentiment influence. , 2014, Journal of the American Medical Informatics Association : JAMIA.

[6]  James Caverlee,et al.  Who is the barbecue king of texas?: a geo-spatial approach to finding local experts on twitter , 2014, SIGIR.

[7]  Samee Ullah Khan,et al.  Elements of Cloud Adoption , 2014, IEEE Cloud Computing.

[8]  Mazliza Othman,et al.  A Survey of Mobile Cloud Computing Application Models , 2014, IEEE Communications Surveys & Tutorials.

[9]  Samee Ullah Khan,et al.  > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 1 , 2008 .

[10]  Meredith A Barrett,et al.  Big Data and Disease Prevention: From Quantified Self to Quantified Communities , 2013, Big Data.

[11]  Vern Paxson,et al.  Trafficking Fraudulent Accounts: The Role of the Underground Market in Twitter Spam and Abuse , 2013, USENIX Security Symposium.

[12]  Darcy A. Davis,et al.  Bringing Big Data to Personalized Healthcare: A Patient-Centered Framework , 2013, Journal of General Internal Medicine.

[13]  Krishna P. Gummadi,et al.  Cognos: crowdsourcing search for topic experts in microblogs , 2012, SIGIR '12.

[14]  Enrique Herrera-Viedma,et al.  A hybrid recommender system for the selective dissemination of research resources in a Technology Transfer Office , 2012, Inf. Sci..

[15]  Mohammad Khalilia,et al.  Predicting disease risks from highly imbalanced data using random forest , 2011, BMC Medical Informatics Decis. Mak..

[16]  Kyumin Lee,et al.  Seven Months with the Devils: A Long-Term Study of Content Polluters on Twitter , 2011, ICWSM.

[17]  Shyam Visweswaran,et al.  The application of naive Bayes model averaging to predict Alzheimer's disease from genome-wide data , 2011, J. Am. Medical Informatics Assoc..

[18]  Scott Counts,et al.  Identifying topical authorities in microblogs , 2011, WSDM '11.

[19]  Z. Hasan A Survey on Shari’Ah Governance Practices in Malaysia, GCC Countries and the UK , 2011 .

[20]  Gholam Ali Montazer,et al.  A fuzzy-evidential hybrid inference engine for coronary heart disease risk assessment , 2010, Expert Syst. Appl..

[21]  Alex Hai Wang,et al.  Don't follow me: Spam detection in Twitter , 2010, 2010 International Conference on Security and Cryptography (SECRYPT).

[22]  E. David,et al.  Networks, Crowds, and Markets: Reasoning about a Highly Connected World , 2010 .

[23]  Muin J. Khoury,et al.  Application of support vector machine modeling for prediction of common diseases: the case of diabetes and pre-diabetes , 2010, BMC Medical Informatics Decis. Mak..

[24]  David M. Eddy,et al.  Diabetes Risk Calculator , 2008, Diabetes Care.

[25]  Sellappan Palaniappan,et al.  Intelligent heart disease prediction system using data mining techniques , 2008, 2008 IEEE/ACS International Conference on Computer Systems and Applications.

[26]  E. Todeva Networks , 2007 .

[27]  J. G. Liao,et al.  Logistic regression for disease classification using microarray data: model selection in a large p and small n case , 2007, Bioinform..

[28]  Juan José Rodríguez Diez,et al.  Rotation Forest: A New Classifier Ensemble Method , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[29]  Yingtao Jiang,et al.  A multilayer perceptron-based medical decision support system for heart disease diagnosis , 2006, Expert Syst. Appl..

[30]  Jaakko Tuomilehto,et al.  The diabetes risk score: a practical tool to predict type 2 diabetes risk. , 2003, Diabetes care.

[31]  John Riedl,et al.  Item-based collaborative filtering recommendation algorithms , 2001, WWW '01.

[32]  George A. Miller,et al.  WordNet: A Lexical Database for English , 1995, HLT.

[33]  E. H. Jarow Clouds , 1931, Nature.

[34]  Basel Kayyali,et al.  The big-data revolution in US health care : Accelerating value and innovation April 2013 , 2013 .

[35]  Punam Bedi,et al.  Trust based recommender system using ant colony for trust computation , 2012, Expert Syst. Appl..

[36]  Ishfaq Ahmad,et al.  A Theoretical Analysis of Scalability of the Parallel Genome Assembly Algorithms , 2011, BIOINFORMATICS.

[37]  William H. Dutton,et al.  Clouds, big data, and smart assets: Ten tech-enabled business trends to watch , 2010 .

[38]  Remco R. Bouckaert,et al.  Bayesian Network Classifiers in Weka for Version 3-5-7 , 2007 .

[39]  Haijia Shi Best-first Decision Tree Learning , 2007 .

[40]  Samee Ullah Khan,et al.  Future Generation Computer Systems ( ) – Future Generation Computer Systems a Cloud Based Health Insurance Plan Recommendation System: a User Centered Approach , 2022 .