k-fold Subsampling based Sequential Backward Feature Elimination

We present a new wrapper feature selection algorithm for human detection. This algorithm is a hybrid featureselection approach combining the benefits of filter and wrapper methods. It allows the selection of an optimalfeature vector that well represents the shapes of the subjects in the images. In detail, the proposed featureselection algorithm adopts the k-fold subsampling and sequential backward elimination approach, while thestandard linear support vector machine (SVM) is used as the classifier for human detection. We apply theproposed algorithm to the publicly accessible INRIA and ETH pedestrian full image datasets with the PASCALVOC evaluation criteria. Compared to other state of the arts algorithms, our feature selection based approachcan improve the detection speed of the SVM classifier by over 50% with up to 2% better detection accuracy.Our algorithm also outperforms the equivalent systems introduced in the deformable part model approach witharound 9% improvement in the detection accuracy

Acute care teaching in the undergraduate nursing curriculum

AIM: To incorporate basic aspects of acute care into the undergraduate nursing programme by providing an opportunity for the development of knowledge and skills in the early recognition and assessment of deteriorating patients on general hospital wards.
BACKGROUND: Acute care initiatives implemented in the hospital setting to improve the identification and management of 'at risk' patients have focused on the provision of education for trained or qualified staff. However, to ensure student nurses are 'fit to practice' at the point of registration, it has been recommended that acute care theory and skills are incorporated into the undergraduate nursing curriculum.
PRACTICE DEVELOPMENT INITIATIVE: An 'Integrated Nursing Care' module was incorporated into year 3 of the undergraduate nursing programme to introduce students to acute care theory and practice. Module content focuses on the early detection and management of acute deterioration in patients with respiratory, cardiac, neurological or renal insufficiencies. We used a competency-based framework to ensure the application of theory to practice through the use of group seminars. High-fidelity patient-simulated clinical scenarios were a key feature. The United Kingdom Resuscitation Council Intermediate Life Support course is also an important component of the module.
CONCLUSIONS: Incorporating the Integrated Nursing Care module into the undergraduate nursing curriculum provides pre-registration students the opportunity to develop their knowledge and skills in acute care.
RELEVANCE TO CLINICAL PRACTICE: The provision of undergraduate education in care of the acutely ill patient in hospital is essential to improve nurses' competence and confidence in assessing and managing deteriorating patients in general wards at the point of registration.