AIMC Topic: New Zealand

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A machine learning model for predicting risk of hospital readmission within 30 days of discharge: validated with LACE index and patient at risk of hospital readmission (PARR) model.

Medical & biological engineering & computing
The objective of this study was to design and develop a predictive model for 30-day risk of hospital readmission using machine learning techniques. The proposed predictive model was then validated with the two most commonly used risk of readmission m...

A predictive model of recreational water quality based on adaptive synthetic sampling algorithms and machine learning.

Water research
Predicting recreational water quality is one of the most difficult tasks in water management with major implications for humans and society. Many data-driven models have been used to predict water quality indicators to allow a real time assessment of...

Towards implementation of AI in New Zealand national diabetic screening program: Cloud-based, robust, and bespoke.

PloS one
Convolutional Neural Networks (CNNs) have become a prominent method of AI implementation in medical classification tasks. Grading Diabetic Retinopathy (DR) has been at the forefront of the development of AI for ophthalmology. However, major obstacles...

Characterization of phenolic compounds and aroma active compounds in feijoa juice from four New Zealand grown cultivars by LC-MS and HS-SPME-GC-O-MS.

Food research international (Ottawa, Ont.)
The phenolic compounds and aroma active compounds in feijoa (Acca sellowiana (O.Berg) Burret) juice from four New Zealand grown cultivars (Apollo, Unique, Opal Star, and Wiki Tu) were investigated. A high total phenolic content (maximum 1.89 mg GAE/m...

Using machine learning techniques to develop risk prediction models to predict graft failure following kidney transplantation: protocol for a retrospective cohort study.

F1000Research
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...

A comparison of machine learning and logistic regression in modelling the association of body condition score and submission rate.

Preventive veterinary medicine
The effect of body condition score (BCS) on reproductive outcomes is complex, dynamic and non-linear with interaction and confounding. The flexibility inherent in machine learning algorithms makes them attractive for analysing complex data. This stud...

Experimental infection of Friesian bulls with Theileria orientalis (Ikeda) and effects on the haematocrit, live weight, rectal temperature and activity.

Veterinary parasitology, regional studies and reports
Since 2012, New Zealand has suffered from an epidemic of infectious bovine anaemia associated with T. orientalis (Ikeda), an obligate intracellular protozoan parasite of cattle. Despite widespread agreement that T. orientalis (Ikeda) infection has im...

Homecare Robots to Improve Health and Well-Being in Mild Cognitive Impairment and Early Stage Dementia: Results From a Scoping Study.

Journal of the American Medical Directors Association
OBJECTIVES: This scoping study is the first step of a multiphase, international project aimed at designing a homecare robot that can provide functional support, track physical and psychological well-being, and deliver therapeutic intervention specifi...

A Pilot Randomized Trial of a Companion Robot for People With Dementia Living in the Community.

Journal of the American Medical Directors Association
OBJECTIVES: To investigate the affective, social, behavioral, and physiological effects of the companion robot Paro for people with dementia in both a day care center and a home setting.