AI technologies can pose a major national security concern. AI programs could be used to develop chemical and biological agents which circumvent existing protective measures or medical treatments, or to design pathogens with capabilities they do not ...
BACKGROUND: Malnutrition is a prevalent issue in aged care facilities (RACFs), leading to adverse health outcomes. The ability to efficiently extract key clinical information from a large volume of data in electronic health records (EHR) can improve ...
We developed a high-resolution machine learning based surrogate model to identify a robust land-use future for Australia which meets multiple UN Sustainable Development Goals. We compared machine learning models with different architectures to pick t...
Liver international : official journal of the International Association for the Study of the Liver
39046171
BACKGROUND: Hepatocellular carcinoma (HCC) recurrence following surgical resection remains a significant clinical challenge, necessitating reliable predictive models to guide personalised interventions. In this study, we sought to harness the power o...
Precision in grazing management is highly dependent on accurate pasture monitoring. Typically, this is often overlooked because existing approaches are labour-intensive, need calibration, and are commonly perceived as inaccurate. Machine-learning pro...
International journal of medical informatics
39003790
OBJECTIVE: To determine the incidence of patients presenting in pain to a large Australian inner-city emergency department (ED) using a clinical text deep learning algorithm.
AIM: This qualitative study aims to explore the perspectives of nursing students regarding the application and integration of generative Artificial Intelligence (AI) tools in their studies.
BACKGROUND: The reporting of adverse events (AEs) relating to medical devices is a long-standing area of concern, with suboptimal reporting due to a range of factors including a failure to recognize the association of AEs with medical devices, lack o...
Journal of epidemiology and community health
38839108
BACKGROUND: Gender influences cardiovascular disease (CVD) through norms, social relations, roles and behaviours. This study identified gender-specific aspects of socialisation associated with CVD.