AIMC Topic: New South Wales

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StUdy of Gestational diabetes And Risk using Electronic Data (SUGARED): a population-based cohort study-study protocol.

BMJ open Dec 26, 2024
INTRODUCTION: The incidence of gestational diabetes mellitus (GDM) in Australia has tripled in the last 20 years. Consequently, over 40 000 pregnancies are now diagnosed as 'higher risk' each year. This has increased antenatal surveillance and obstet...
Pregnancy Outcome Logistic Models Observational Studies as Topic Diabetes, Gestational Pregnancy Female Risk Assessment Incidence Multilevel Analysis New South Wales Hospitals, Public Routinely Collected Health Data Predictive Learning Models Glucose Tolerance Test Information Storage and Retrieval Propensity Score Delivery, Obstetric Humans Research Design Retrospective Studies
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Accounting for minimum data required to train a machine learning model to accurately monitor Australian dairy pastures using remote sensing.

Scientific reports Jul 23, 2024
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...
Biomass Cattle Australia Remote Sensing Technology Dairying Machine Learning New South Wales Animals
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Protocol for evaluating the fitness for purpose of an artificial intelligence product for radiology reporting in the BreastScreen New South Wales breast cancer screening programme.

BMJ open May 28, 2024
INTRODUCTION: Radiologist shortages threaten the sustainability of breast cancer screening programmes. Artificial intelligence (AI) products that can interpret mammograms could mitigate this risk. While previous studies have suggested this technology...
Humans Artificial Intelligence Research Design Retrospective Studies Female Mammography Breast Neoplasms New South Wales Middle Aged Mass Screening Early Detection of Cancer
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Predictive analytics for cardiovascular patient readmission and mortality: An explainable approach.

Computers in biology and medicine Mar 20, 2024
BACKGROUND: Cardiovascular patients experience high rates of adverse outcomes following discharge from hospital, which may be preventable through early identification and targeted action. This study aimed to investigate the effectiveness and explaina...
Aged Aged, 80 and over Adult Male Machine Learning Algorithms Female Risk Factors Cardiovascular Diseases Middle Aged Patient Readmission New South Wales Humans
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The Sydney Triage to Admission Risk Tool (START2) using machine learning techniques to support disposition decision-making.

Emergency medicine Australasia : EMA Nov 23, 2018
OBJECTIVE: To further develop and refine an Emergency Department (ED) in-patient admission prediction model using machine learning techniques.
ROC Curve Logistic Models Triage Area Under Curve Patient Admission New South Wales Adult Emergency Service, Hospital Male Bayes Theorem Middle Aged Adolescent Retrospective Studies Female Humans Aged Machine Learning Aged, 80 and over Forecasting
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Extracting cancer mortality statistics from death certificates: A hybrid machine learning and rule-based approach for common and rare cancers.

Artificial intelligence in medicine May 10, 2018
OBJECTIVE: Death certificates are an invaluable source of cancer mortality statistics. However, this value can only be realised if accurate, quantitative data can be extracted from certificates-an aim hampered by both the volume and variable quality ...
Registries Data Mining Data Accuracy Rare Diseases New South Wales Neoplasms Humans Death Certificates Support Vector Machine Databases, Factual Natural Language Processing Reproducibility of Results Cause of Death
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A trial of retrofitted advisory collision avoidance technology in government fleet vehicles.

Accident; analysis and prevention Mar 13, 2018
In-vehicle collision avoidance technology (CAT) has the potential to prevent crash involvement. In 2015, Transport for New South Wales undertook a trial of a Mobileye 560 CAT system that was installed in 34 government fleet vehicles for a period of s...
Male Emergencies Surveys and Questionnaires Accidents, Traffic Attitude Protective Devices New South Wales Safety Automobile Driving Artificial Intelligence Technology Female Adult Humans Motor Vehicles
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Coronary artery disease risk assessment from unstructured electronic health records using text mining.

Journal of biomedical informatics Aug 28, 2015
Coronary artery disease (CAD) often leads to myocardial infarction, which may be fatal. Risk factors can be used to predict CAD, which may subsequently lead to prevention or early intervention. Patient data such as co-morbidities, medication history,...
Cardiovascular Diseases Middle Aged Risk Assessment Comorbidity Electronic Health Records Female Humans Aged Vocabulary, Controlled Diabetes Complications Male Natural Language Processing New South Wales Confidentiality Data Mining Incidence Pattern Recognition, Automated Cohort Studies Computer Security Longitudinal Studies Narration
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Automatic ICD-10 classification of cancers from free-text death certificates.

International journal of medical informatics Aug 13, 2015
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 certificates--an aim hampered by both the volume and variable na...
Neoplasms Humans New South Wales Natural Language Processing Machine Learning International Classification of Diseases Death Certificates Cause of Death Program Evaluation Registries
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Automatic classification of diseases from free-text death certificates for real-time surveillance.

BMC medical informatics and decision making Jul 15, 2015
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 the development and monitoring of prevention or response strate...
New South Wales Death Certificates Humans Machine Learning Classification Epidemiological Monitoring
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