Efficient storage and management of medical supplies reduces the time clinical staff have to spend on routine logistical functions and decreases the chance of accidentally choosing the wrong medication for a patient. When a patient is admitted to hospital, the efficient storage and management of pharmaceutical medical supplies is likely to be the last thing
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
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
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
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
Named-Entity Recognition (NER) is still a challenging task for languages with low digital resources. The main difficulties arise from the scarcity of annotated corpora and the consequent problematic training of an effective NER pipeline. To abridge this gap, in this paper we target the Persian language that is spoken by a population of over a
Researchers produce a new framework, StreamEB, which could revolutionise the visual analysis of data and graph streams. Dr Quan Nguyen CMCRC PhD graduate U. of Sydney Prof Peter Eades CMCRC Research Leader U. of Sydney High velocity data streams such as trading data have become ubiquitous since the 1990s and graph streaming is becoming
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
The healthcare sector deals with large volumes of electronic data related to patient services. This article describes two novel applications that leverage big data to detect fraud, abuse, waste, and errors in health insurance claims, thus reducing recurrent losses and facilitating enhanced patient care. The results indicate that claim anomalies detected using these applications help
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