Background: Interoperability and secondary use of data is a challenge in health care.
Specifically, the reuse of clinical free text remains an unresolved problem. The Systematized …

Artificial intelligence (AI) is having an increasing impact on the field of pathology, as
computation techniques allow computers to perform tasks previously performed by people …

Objective Death certificates provide an invaluable source for cancer mortality statistics;
however, this value can only be realised if accurate, quantitative data can be extracted from …

Objective This paper presents an automatic, active learning-based system for the extraction
of medical concepts from clinical free-text reports. Specifically,(1) the contribution of active …

Background 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 …

Cancer Registries record cancer data by reading and interpreting pathology cancer
specimen reports. For some Registries this can be a manual process, which is labour and …

Objective To develop and evaluate machine learning techniques that identify limb fractures
and other abnormalities (eg dislocations) from radiology reports. Materials and Methods 99 …

Background Cancer monitoring and prevention relies on the critical aspect of timely
notification of cancer cases. However, the abstraction and classification of cancer from the …

The paper assesses the utility of Medtex on automating Cancer Registry notifications from
narrative histology and cytology reports from the Queensland state-wide pathology …

We study machine learning techniques to automatically identify limb abnormalities
(including fractures, dislocations and foreign bodies) from radiology reports. For patients …