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Category: Papers

APPLICATION OF NETWORK ANALYSIS ON HEALTHCARE

Fei Wang, Uma Srinivasan, Shahadat Uddin, and Sanjay Chawla. “Application of network analysis on healthcare”. In Advances in Social Networks Analysis and Mining (ASONAM), 2013 IEEE/ACM International Conference on IEEE, 2014. The healthcare sector holds large amounts of semantically rich electronic data generated and used by different sections of the health care community. Data analytic

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TIKHONOV OR LASSO REGULARIZATION: WHICH IS BETTER AND WHEN. IN TOOLS WITH ARTIFICIAL INTELLIGENCE

Fei Wang, Sanjay Chawla, and Wei Liu. “Tikhonov or lasso regularization: Which is better and when. In Tools with Artificial Intelligence” (ICTAI), 2013 IEEE 25th International Conference on, pages 795–802. IEEE, 2013. It is well known that supervised learning problems with ℓ1 (Lasso) and ℓ2 (Tikhonov or Ridge) regularizers will result in very different solutions. For example,

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DATA SCIENCE AND THE POLICY COMPLETION PROBLEM

Sanjay Chawla, Federico Girosi, Fei Wang “Data Science and the Policy Completion Problem” The link between policy analysis and data science is more delicate than it may appear. A new policy, by definition, will change the underlying data generating model, rendering classification or supervised learning inapplicable. Perhaps eliciting causal relations from observational data is the

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MULTI-FUND DATA ANALYTICS TARGETS ENHANCED VALUE-FOR-MONEY IN HEALTHCARE SERVICES

Governments as well as health and accident compensation insurers are grappling to improve health outcomes while keeping spiraling costs under control. These seemingly irreconcilable goals require a careful balance of policy to help stem the tide of ever increasing costs in the health industry. Dr Uma Srinivasan CMC Insurance Solutions CMC Lead Scientist   Keywords: Health insurance,

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SOCIAL NETWORK RESEARCH IN HEALTH COULD OPEN THE DOOR FOR SIGNIFICANT SAVINGS

The health industry consumes vast amounts of money and resources and is seen as a “black-hole” in many Government budgets. A ground breaking study using new science could save the industry millions and point the way for future research. Dr Shahadat Uddin CMCRC PhD Graduate Lecturer, U. Sydney Shahadat Uddin is a graduate of the

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JOINT APPOSITION EXTRACTION WITH SYNTACTIC AND SEMANTIC CONSTRAINTS

A study by CMCRC researchers presents a fresh look at extracting apposition from large collections of news, web and broadcast text in order to turn unstructured news stories into “computable data”. News is about interactions between entities ‐ people, places and organisations ‐ and understanding stories requires interpreting the entities in them and their attributes.

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MAKER-TAKER FEE, LIQUIDITY COMPETITION, AND HIGH FREQUENCY TRADING

This paper analyzes how a maker-taker fee reduction affects market competition, liquidity, and high frequency trading. The purposes are threefold: 1) whether reducing the exchange maker-taker fee attracts liquidity from off-exchange venues; 2) holding the net exchange fee relatively constant, whether the components of the maker-taker fee change matter; and 3) how HFT responds to

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DATA MINING RESEARCHERS USE INNOVATIVE TECHNIQUES TO BUILD ROBUST CLASSIFIER

Researcher discovers that a combination of adversarial learning and sparse modelling techniques improves the performance of an email/spam classifier. Fei Wang CMCRC PhD candidate U. of Sydney Prof Sanjay Chawla CMCRC Research Leader U. of Sydney   Classifiers are widely used in many computer-based applications to the bene- fit of virtually all computer users. An

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UNDERSTANDING CHRONIC DISEASE COMORBIDITIES FROM BASELINE NETWORKS – KNOWLEDGE DISCOVERY UTILISING ADMINISTRATIVE HEALTHCARE DATA

Hospitals routinely collect admitted patients’ data for administrative purposes and for reporting to the government and health insurers. These heterogeneous and mostly untapped data contain rich semantic information about patients’ health conditions in the form of standard disease codes. These traces of clinical information can be aggregated over patients to understand how their health progresses

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COMPUTER SCIENCE RESEARCH PRODUCES NEW TYPE OF REGRESSION ALGORITHM FOR STOCK PICKING

Study looks at combining text data and financial quantitative data to produce a model for predicting a stocks daily return. Tony Zhao Zhao is a PhD student at Macquarie University. He has worked on a wide range of topics including embedded systems, digital signal processing, machine learning, large-scale data processing and natural language processing but

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