AIMC Topic: Australia
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Predicting alcohol dependence treatment outcomes: a prospective comparative study of clinical psychologists versus 'trained' machine learning models.
Addiction (Abingdon, England)
Mar 26, 2020
BACKGROUND AND AIMS: Clinical staff are typically poor at predicting alcohol dependence treatment outcomes. Machine learning (ML) offers the potential to model complex clinical data more effectively. This study tested the predictive accuracy of ML al...
The Effect of Using PARO for People Living With Dementia and Chronic Pain: A Pilot Randomized Controlled Trial.
Journal of the American Medical Directors Association
Feb 29, 2020
OBJECTIVES: To evaluate the effect of interaction with a robotic seal (PARO) on pain and behavioral and psychological symptoms of people with dementia and chronic pain.
The application of artificial intelligence (AI) techniques to identify frailty within a residential aged care administrative data set.
International journal of medical informatics
Feb 4, 2020
INTRODUCTION: Research has shown that frailty, a geriatric syndrome associated with an increased risk of negative outcomes for older people, is highly prevalent among residents of residential aged care facilities (also called long term care facilitie...
Automatic Hierarchical Classification of Kelps Using Deep Residual Features.
Sensors (Basel, Switzerland)
Jan 13, 2020
Across the globe, remote image data is rapidly being collected for the assessment of benthic communities from shallow to extremely deep waters on continental slopes to the abyssal seas. Exploiting this data is presently limited by the time it takes f...
Deep learning for pollen allergy surveillance from twitter in Australia.
BMC medical informatics and decision making
Nov 8, 2019
BACKGROUND: The paper introduces a deep learning-based approach for real-time detection and insights generation about one of the most prevalent chronic conditions in Australia - Pollen allergy. The popular social media platform is used for data colle...
Using machine learning techniques to develop risk prediction models to predict graft failure following kidney transplantation: protocol for a retrospective cohort study.
F1000Research
Oct 29, 2019
A mechanism to predict graft failure before the actual kidney transplantation occurs is crucial to clinical management of chronic kidney disease patients. Several kidney graft outcome prediction models, developed using machine learning methods, are...
Predicting diabetes second-line therapy initiation in the Australian population via time span-guided neural attention network.
PloS one
Oct 18, 2019
INTRODUCTION: The first line of treatment for people with Diabetes mellitus is metformin. However, over the course of the disease metformin may fail to achieve appropriate glycemic control, and a second-line therapy may become necessary. In this pape...
The ethical, legal and social implications of using artificial intelligence systems in breast cancer care.
Breast (Edinburgh, Scotland)
Oct 11, 2019
Breast cancer care is a leading area for development of artificial intelligence (AI), with applications including screening and diagnosis, risk calculation, prognostication and clinical decision-support, management planning, and precision medicine. W...
Exploring healthcare professionals' understanding and experiences of artificial intelligence technology use in the delivery of healthcare: An integrative review.
Health informatics journal
Sep 30, 2019
BACKGROUND: The integration of artificial intelligence (AI) into our digital healthcare system is seen as a significant strategy to contain Australia's rising healthcare costs, support clinical decision making, manage chronic disease burden and suppo...
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