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Tag: DHCRC

ADAPTING GRAPH THEORY AND SOCIAL NETWORK MEASURES ON HEALTHCARE DATA – A NEW FRAMEWORK TO UNDERSTAND CHRONIC DISEASE PROGRESSION

The paper presents an approach that applies social network theory to understand chronic disease progression. Submitted to the Australasian Workshop on Health Informatics and Knowledge Management  https://cs.anu.edu.au/conf/acsw2016/sub-confs/hikm.html Author(s): Arif Khan, Shahadat Uddin and Uma Srinivasan

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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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A FRAMEWORK FOR ADMINISTRATIVE CLAIM DATA TO EXPLORE HEALTHCARE COORDINATION AND COLLABORATION

Previous studies have documented the application of electronic health insurance claim data for health services research purposes. In addition to administrative and billing details of healthcare services, insurance data reveal important information regarding professional interactions/links that emerge among healthcare service providers through, for example, informal knowledge sharing. By utilising details of such professional interactions and

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CASE-MIX BASED PEER CLUSTERING

We consider the problem of clustering hospitals based on their case-mix distributions. Hospitals belong to the same cluster if they offer the same mix of services and have similar demand for those services. The cluster labels can be used to control for case-mix in hospital level analyses. Methods: We obtained distributions of the 770 AR-DRGv7.0 for

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AN APPROACH TO EMPOWER PATIENTS TO MANAGE DIABETES

Timely information and education can enhance the ability of consumers to make informed choices about their health, lifestyle and modifiable disease risk factors. Due to its unstructured and varied format, and lack of targeted delivery methods, information and knowledge does not often reach consumers, when they need it most. The aim of this project is

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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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MODELLING THE TREATMENT PATHWAY OF HER2-POSITIVE METASTATIC BREAST CANCER (HER2+MBC) IN AUSTRALIA, 2001 – 2015

Speaker: Benjamin Daniels, UNSW Seminar Date: Tuesday October 24 12:00pm Brief abstract: Background: Metastatic cancer and its treatment are conceptualised in terms of “stages”. Clinical trials and most observational research are concerned with what is often just one stage out of several. In this project we attempt to use routinely collected Australian administrative health data to associate survival outcomes

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