Anthony Nguyen
Team Leader
Health Text Analytics
The Health Text Analytics team is at the forefront of research and development in the use of text retrieval and analytics techniques for unlocking the value from unstructured electronic health records.
Our Science
We develop and apply advanced natural language processing, information retrieval and machine learning techniques, along with standard clinical terminology (e.g. SNOMED CT) semantics and reasoning, to provide meaningful and accurate computational interpretation of clinical free-text.
Key challenges include:
Impact on the Health System
We deliver and support meaningful data interoperability and analysis for decision support, analytics, modeling and reporting to improve patient outcomes, health system performance and productivity.
Our Solutions
Our solutions have been developed in partnership with healthcare practitioners from Cancer Registries, hospital radiology and emergency medicine departments. It leverages the wealth of clinical free-text reports from health industry stakeholders to aid in decision support and reporting.
Our research has developed advanced natural language processing, information retrieval, and machine learning approaches to overcome the problems of ‘understanding and reasoning with clinical data’. Medical Free Text...
The Challenge Adverse Drug Reactions (ADRs), also known as drug side effects, are a major concern for public health, costing health care systems worldwide millions of dollars. Social media has been identified as a source of information...
The Challenge Search technologies are critical to enable clinical staff to rapidly and effectively access patient information contained in free-text medical records. Medical search is challenging as it suffers from the semantic gap...
The Challenge The checking of X-ray reports to ensure limb fractures are not missed and that patients receive appropriate follow-up once discharged from the Emergency Department (ED) is an essential but laborious task....
The Challenge Death certificates provide an invaluable source for mortality statistics, which can be used for surveillance and early warnings of increases in disease activity and to support the development and monitoring of prevention...
Pathology notification for a Cancer Registry is regarded as the most valid information for the confirmation of a diagnosis of cancer. The development of a clinical decision support system to unlock information from medical free-text...
The challenge: Adopting the international standard for healthcare data Electronic management of health information promises safer, more efficient and better quality healthcare. However, different health records often use various terms...
The challenge: Incompatible health data Australia’s health care system faces many challenges. One is the increasing demand for clinical information to be shared between individual health practitioners, health care provider...
Team Members
Anthony Nguyen
Bevan Koopman
Hamed Hassanzadeh
Anthony Nguyen
Development and application of novel solutions for the medical text analysis of pathology, radiology, discharge, and other clinical reports to support clinical decision-making.
CSIRO Profile
Bevan Koopman
Research and development of new search engine models to improve the access, delivery and quality of health information to the people who need it.
CSIRO Profile
Hamed Hassanzedah
Research and development of novel text analytics solutions using machine learning, natural language processing, information extraction, semantic similarities and ontologies for Evidence Based Medicine.
CSIRO Profile
