Use of computer-aided detection (CAD) tools in screening mammography: a multidisciplinary investigation

We summarise a set of analyses and studies conducted to assess the effects of the use of a computer-aided detection (CAD) tool in breast screening. We have used an interdisciplinary approach that combines: (a) statistical analyses inspired by reliability modelling in engineering; (b) experimental studies of decisions of mammography experts using the tool, interpreted in the light of human factors psychology; and (c) ethnographic observations of the use of the tool both in trial conditions and in everyday screening practice. Our investigations have shown patterns of human behaviour and effects of computer-based advice that would not have been revealed by a standard clinical trial approach. For example, we found that the negligible measured effect of CAD could be explained by a range of effects on experts' decisions, beneficial in some cases and detrimental in others. There is some evidence of the latter effects being due to the experts using the computer tool differently from the intentions of the developers. We integrate insights from the different pieces of evidence and highlight their implications for the design, evaluation and deployment of this sort of computer tool

The effect of multidisciplinary collaborations on research diversification

This work verifies whether research diversification by a scientist is in some measure related to their collaboration with multidisciplinary teams. The analysis considers the publications achieved by 5300 Italian academics in the sciences over the period 2004-2008. The findings show that a scientist's outputs resulting from research diversification are more often than not the result of collaborations with multidisciplinary teams. The effect becomes more pronounced with larger and particularly with more diversified teams. This phenomenon is observed both at the overall level and for the disciplinary macro-areas

An Integrated Method for Determination of the Oswald Factor in a Multi-Fidelity Design Environment

Aircraft conceptual design often focuses on unconventional configurations like for example forward swept wings. Assessing the characteristics of these configurations usually requires the use of physic based analysis modules. This is due to the fact that for unconventional configurations no sucient database for historic based analysis modules is available. Nevertheless, physic based models require a lot of input data and their computational cost can be high. Generating input values in a trade study manually is work-intensive and error-prone. Conceptual design modules can be used to generate sucient input data for physic based models and their results can be re-integrated into the conceptual design phase. In this study a direct link between a conceptual design module and an aerodynamic design module is presented. Geometric information is generated by the conceptual design module and the physic based results, in form of the Oswald factor, are then fed back. Apart from the direct link, an equation for determination of the Oswald factor is derived via a Symbolic Regression Approach