[HTML][HTML] Use of the systematized nomenclature of medicine clinical terms (SNOMED CT) for processing free text in health care: systematic scoping review
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 …
Specifically, the reuse of clinical free text remains an unresolved problem. The Systematized …
Artificial intelligence in pathology: a simple and practical guide
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 …
computation techniques allow computers to perform tasks previously performed by people …
Automatic ICD-10 classification of cancers from free-text death certificates
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 …
however, this value can only be realised if accurate, quantitative data can be extracted from …
Active learning: a step towards automating medical concept extraction
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 …
of medical concepts from clinical free-text reports. Specifically,(1) the contribution of active …
[HTML][HTML] Automatic classification of diseases from free-text death certificates for real-time surveillance
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 …
be used for surveillance and early warnings of increases in disease activity and to support …
[HTML][HTML] Assessing the utility of automatic cancer registry notifications data extraction from free-text pathology reports
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 …
specimen reports. For some Registries this can be a manual process, which is labour and …
[HTML][HTML] Automatic classification of free-text radiology reports to identify limb fractures using machine learning and the snomed ct ontology
Objective To develop and evaluate machine learning techniques that identify limb fractures
and other abnormalities (eg dislocations) from radiology reports. Materials and Methods 99 …
and other abnormalities (eg dislocations) from radiology reports. Materials and Methods 99 …
[HTML][HTML] Classification of cancer-related death certificates using machine learning
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 …
notification of cancer cases. However, the abstraction and classification of cancer from the …
[HTML][HTML] Automated cancer registry notifications: validation of a medical text analytics system for identifying patients with cancer from a state-wide pathology repository
The paper assesses the utility of Medtex on automating Cancer Registry notifications from
narrative histology and cytology reports from the Queensland state-wide pathology …
narrative histology and cytology reports from the Queensland state-wide pathology …
[HTML][HTML] Automated reconciliation of radiology reports and discharge summaries
We study machine learning techniques to automatically identify limb abnormalities
(including fractures, dislocations and foreign bodies) from radiology reports. For patients …
(including fractures, dislocations and foreign bodies) from radiology reports. For patients …