AIMC Topic: Artificial Intelligence

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Implementation of Artificial Intelligence Applications in Australian Healthcare Organisations: Environmental Scan Findings.

Studies in health technology and informatics
Artificial Intelligence (AI) has great potential to improve healthcare, but implementation into routine practice remains a challenge. This study scoped the extent to which AI and Natural Language Processing (NLP) is being implemented into routine pra...

Reshaping Wound Care: Evaluation of an Artificial Intelligence App to Improve Wound Assessment and Management.

Studies in health technology and informatics
This study evaluated the usability and effectiveness of an artificial intelligence application for wound assessment and management from a clinician-and-patient perspective. A quasi-experimental design was conducted in four settings in an Australian h...

Whole-Liver Based Deep Learning for Preoperatively Predicting Overall Survival in Patients with Hepatocellular Carcinoma.

Studies in health technology and informatics
Survival prediction is crucial for treatment decision making in hepatocellular carcinoma (HCC). We aimed to build a fully automated artificial intelligence system (FAIS) that mines whole-liver information to predict overall survival of HCC. We includ...

Explainable Artificial Intelligence for Deep-Learning Based Classification of Cystic Fibrosis Lung Changes in MRI.

Studies in health technology and informatics
Algorithms increasing the transparence and explain ability of neural networks are gaining more popularity. Applying them to custom neural network architectures and complex medical problems remains challenging. In this work, several algorithms such as...

Artificial Intelligence Approach for Severe Dengue Early Warning System.

Studies in health technology and informatics
Dengue fever is a viral infectious disease transmitted through mosquito bites, and has symptoms ranging from mild flu-like symptoms to deadly complications. Dengue fever is one of the global burden diseases which annually have 50-100 million cases wi...

Elucidating Discrepancy in Explanations of Predictive Models Developed Using EMR.

Studies in health technology and informatics
The lack of transparency and explainability hinders the clinical adoption of Machine learning (ML) algorithms. While explainable artificial intelligence (XAI) methods have been proposed, little research has focused on the agreement between these meth...

Making Digital Health Equitable.

Studies in health technology and informatics
Most agree that the current healthcare system is broken. Fortunately, technology is increasing at an exponential rate and provides a solution for the future. Digital Health is an integrator concept that has the potential to take advantage of technolo...

Using Clinical Simulation to Evaluate AI-Enabled Decision Support.

Studies in health technology and informatics
Clinical simulation is a useful method for evaluating AI-enabled clinical decision support (CDS). Simulation studies permit patient- and risk-free evaluation and far greater experimental control than is possible with clinical studies. The effect of C...