Aims and objectives. This two-part paper aims to identify the main transferable lessons learned from both the quantitative and qualitative evaluations of the KA24 (Knowledge Access 24) service of online databases and selected full text journals for health and social care staff in London and the South-East of England. The quantitative evaluation analysed usage rates and user registration with th...

In real-life applications, neither all the inputs of an algorithm are available at outset, as in offline framework, nor do they occur one by order, online setup. Semi-online is intermediate theoretically and practically significant framework with additional information on successive to address limitations frameworks. One key motivation for studying semi-online algorithms investigate how can imp...

BACKGROUND Patients with rare diseases such as congenital hypogonadotropic hypogonadism (CHH) are dispersed, often challenged to find specialized care and face other health disparities. The internet has the potential to reach a wide audience of rare disease patients and can help connect patients and specialists. Therefore, this study aimed to: (i) determine if web-based platforms could be effec...

BACKGROUND Clinicians are increasingly using electronic sources of evidence to support clinical decision-making; however, there are multiple demands on clinician time, and summarised and synthesised evidence is needed. Clinical Answers (CA) have been developed to address this need; the CA is a synthesised evidence-based summary that supports point-of-care clinical decision-making. The aim of th...

BACKGROUND Persistently variable success has been experienced in locally translating even well-grounded national clinical practice guidelines, including in the perioperative setting. We have sought greater applicability and acceptance of clinical practice guidelines and protocols with our novel Perioperative Risk Optimization and Management Planning Tool (PROMPT™). This study was undertaken to ...

Online learning represents a family of machine methods, where learner attempts to tackle some predictive (or any type decision-making) task by from sequence data instances one at each time. The goal online is maximize the accuracy/correctness for predictions/decisions made given knowledge correct answers previous prediction/learning tasks and possibly additional information. This in contrast tr...