For many respiratory physicians, point-of-care chest ultrasound is now an integral part of clinical practice. The diagnostic accuracy of ultrasound to detect abnormalities of the pleura, the lung parenchyma and the thoracic musculoskeletal system is well described. However, the efficacy of a test extends beyond just diagnostic accuracy. The true value of a test depends on the degree to which di...

BACKGROUND The most rigorous method for evaluating the effectiveness of diagnostic tests is through randomised trials that compare test-treatment interventions: complex interventions comprising episodes of testing, decision-making and treatment. The multi-staged nature of these interventions, combined with the need to relay diagnostic decision-making and treatment planning, has led researchers ...

Measures of diagnostic accuracy, such as sensitivity, specificity, predictive values, and receiver operating characteristic curves, can often seem like abstract mathematic concepts that have a minimal relationship with clinical decision making or clinical research. The purpose of this article is to provide definitions and examples of these concepts that illustrate their usefulness in specific c...

In previous work we showed that the automatic generation of diagnostic decision trees from qualitative models is a reasonable compromise between the advantages of using a model-based approach in automotive domains and the constraints imposed by on-board applications. In this paper we extend the approach to deal with temporal information. We introduce a notion of temporal diagnostic decision tre...

Dentists are involved in diagnosing disease in every aspect of their clinical practice. A range of tests, systems, guides and equipment--which can be generally referred to as diagnostic procedures--are available to aid in diagnostic decision making. In this era of evidence-based dentistry, and given the increasing demand for diagnostic accuracy and properly targeted health care, it is important...

This dissertation discusses three problems from different areas of medical research and their machine learning solutions. Each solution is a distinct type of decision support system. They show three common properties: personalized health care decision support, reduction of the use of medical resources, and improvement of outcomes. The first decision support system assists individual hospital se...