Statistical methods for tissue array images - algorithmic scoring and co-training

Recent advances in tissue microarray technology have allowed immunohistochemistry to become a powerful medium-to-high throughput analysis tool, particularly for the validation of diagnostic and prognostic biomarkers. However, as study size grows, the manual evaluation of these assays becomes a prohibitive limitation; it vastly reduces throughput and greatly increases variability and expense. We propose an algorithm - Tissue Array Co-Occurrence Matrix Analysis (TACOMA) - for quantifying cellular phenotypes based on textural regularity summarized by local inter-pixel relationships. The algorithm can be easily trained for any staining pattern, is absent of sensitive tuning parameters and has the ability to report salient pixels in an image that contribute to its score. Pathologists' input via informative training patches is an important aspect of the algorithm that allows the training for any specific marker or cell type. With co-training, the error rate of TACOMA can be reduced substantially for a very small training sample (e.g., with size 30). We give theoretical insights into the success of co-training via thinning of the feature set in a high-dimensional setting when there is "sufficient" redundancy among the features. TACOMA is flexible, transparent and provides a scoring process that can be evaluated with clarity and confidence. In a study based on an estrogen receptor (ER) marker, we show that TACOMA is comparable to, or outperforms, pathologists' performance in terms of accuracy and repeatability.Comment: Published in at http://dx.doi.org/10.1214/12-AOAS543 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Emergency life support training for school children: exploring local implementation and outcomes of the Heartstart UK school programme within the context of the National Healthy School Standard

This project discusses the implementation of Heartstart UK - an initiative co-ordinated by the British Heart Foundation to increase emergency life support training - in a number of schools in Cheshire.British Heart Foundation

Policies to increase workers skills

Different training policies can serve different objectives. Institutional arrangements to foster cost-sharing can efficiently increase access to formal, accredited and well-recognised training with little burden for the public budget. Co-financing policies that increase the incentive for firms might reduce the possible impact of market failures on aggregate training provision and can be easily financed through specific corporate levies. However, these policies cannot reach those groups that are less likely to receive employer-sponsored training. In this case, co-financing policies targeted to individual demand might become necessary. However, these policies are expensive and might result in substantial waste of public resources if they are not accompanied by interventions to reduce imperfections in the training market.Design is, however, crucial, and it is possible to identify some general principles concerning the desirable characteristics of training policies. Yet, too little is known on their relative efficiency with respect to other potential instruments, due to lack of rigorous evaluation analysis. Hence, taking also into account the methodological complexity of ex-post assessment in this area, evaluation mechanisms should be included into policy design to ensure timely corrections of policy mistakes.training policy