AIMC Topic: Australia
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Cancer survivorship care and general practice: A qualitative study of roles of general practice team members in Australia.
Health & social care in the community
Aug 22, 2021
Primary care providers, including general practice teams (GPTs), are well positioned within the community to integrate cancer survivorship care into ongoing health management. However, roles of GPT members in delivery of cancer survivorship care have...
Legal and ethical considerations of artificial intelligence in skin cancer diagnosis.
The Australasian journal of dermatology
Aug 18, 2021
Artificial intelligence (AI) technology is becoming increasingly accurate and prevalent for the diagnosis of skin cancers. Commercially available AI diagnostic software is entering markets across the world posing new legal and ethical challenges for ...
Real-world artificial intelligence-based opportunistic screening for diabetic retinopathy in endocrinology and indigenous healthcare settings in Australia.
Scientific reports
Aug 4, 2021
This study investigated the diagnostic performance, feasibility, and end-user experiences of an artificial intelligence (AI)-assisted diabetic retinopathy (DR) screening model in real-world Australian healthcare settings. The study consisted of two c...
Use of Multiprognostic Index Domain Scores, Clinical Data, and Machine Learning to Improve 12-Month Mortality Risk Prediction in Older Hospitalized Patients: Prospective Cohort Study.
Journal of medical Internet research
Jun 21, 2021
BACKGROUND: The Multidimensional Prognostic Index (MPI) is an aggregate, comprehensive, geriatric assessment scoring system derived from eight domains that predict adverse outcomes, including 12-month mortality. However, the prediction accuracy of us...
Cost-sensitive learning for semi-supervised hit-and-run analysis.
Accident; analysis and prevention
May 25, 2021
Hit-and-run crashes not only degrade the morality, but also result in delays of medical services provided to victims. However, class imbalance problem exists as the number of hit-and-run crashes is much smaller than that of non-hit-and-run crashes. T...
Tweet Topics and Sentiments Relating to COVID-19 Vaccination Among Australian Twitter Users: Machine Learning Analysis.
Journal of medical Internet research
May 19, 2021
BACKGROUND: COVID-19 is one of the greatest threats to human beings in terms of health care, economy, and society in recent history. Up to this moment, there have been no signs of remission, and there is no proven effective cure. Vaccination is the p...
Spectrofluorometric analysis combined with machine learning for geographical and varietal authentication, and prediction of phenolic compound concentrations in red wine.
Food chemistry
May 18, 2021
Fluorescence spectroscopy is rapid, straightforward, selective, and sensitive, and can provide the molecular fingerprint of a sample based on the presence of various fluorophores. In conjunction with chemometrics, fluorescence techniques have been ap...
Predicting Ambulance Patient Wait Times: A Multicenter Derivation and Validation Study.
Annals of emergency medicine
May 8, 2021
STUDY OBJECTIVE: To derive and internally and externally validate machine-learning models to predict emergency ambulance patient door-to-off-stretcher wait times that are applicable to a wide variety of emergency departments.
A controlled human infection model of Streptococcus pyogenes pharyngitis (CHIVAS-M75): an observational, dose-finding study.
The Lancet. Microbe
Apr 15, 2021
BACKGROUND: Streptococcus pyogenes is a leading cause of infection-related morbidity and mortality. A reinvigorated vaccine development effort calls for new clinically relevant human S pyogenes experimental infection models to support proof of concep...
Technology Acceptance of a Machine Learning Algorithm Predicting Delirium in a Clinical Setting: a Mixed-Methods Study.
Journal of medical systems
Mar 1, 2021
Early identification of patients with life-threatening risks such as delirium is crucial in order to initiate preventive actions as quickly as possible. Despite intense research on machine learning for the prediction of clinical outcomes, the accepta...
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