Spirit, mind and body: the archaeology of monastic healing

Archaeology and material culture are used in this chapter to consider how monastic experience responded to illness, ageing and disability. The approach taken is influenced by the material study of religion, which interrogates how bodies and things engage to construct the sensory experience of religion, and by practice-based approaches in archaeology, which examine the active role of space and material culture in shaping religious agency and embodiment. The archaeology of monastic healing focuses on the full spectrum of healing technologies, from managing the body in order to prevent illness, through to the treatment of the sick and preparation of the corpse for burial

Systematic review on quality control for drug management programs: Is quality reported in the literature?

<p>Abstract</p> <p>Background</p> <p>Maintaining quality of care while managing limited healthcare resources is an ongoing challenge in healthcare. The objective of this study was to evaluate how the impact of drug management programs is reported in the literature and to identify potentially existing quality standards.</p> <p>Methods</p> <p>This analysis relates to the published research on the impact of drug management on economic, clinical, or humanistic outcomes in managed care, indemnity insurance, VA, or Medicaid in the USA published between 1996 and 2007. Included articles were systematically analyzed for study objective, study endpoints, and drug management type. They were further categorized by drug management tool, primary objective, and study endpoints.</p> <p>Results</p> <p>None of the 76 included publications assessed the overall quality of drug management tools. The impact of 9 different drug management tools used alone or in combination was studied in pharmacy claims, medical claims, electronic medical records or survey data from either patient, plan or provider perspective using an average of 2.1 of 11 possible endpoints. A total of 68% of the studies reported the impact on plan focused endpoints, while the clinical, the patient or the provider perspective were studied to a much lower degree (45%, 42% and 12% of the studies). Health outcomes were only accounted for in 9.2% of the studies.</p> <p>Conclusion</p> <p>Comprehensive assessment of quality considering plan, patient and clinical outcomes is not yet applied. There is no defined quality standard. Benchmarks including health outcomes should be determined and used to improve the overall clinical and economic effectiveness of drug management programs.</p

Living in harmony: Designing a multi-functional education facility that has positive sustainable impact on environment and society

A unique way of teaching practical aspects of renewable energy technologies has been experimented in the University of Oldenburg since 1987. An energy laboratory (Energielabor), built in 1982 and powered by renewable energy sources, has been used for practical training, lectures and office space for the staff and students engaged in the field of renewable energy at the University. After 30 years of service, this Energielabor requires revision and needs to be rebuilt to meet the needs of present age. In this direction, as part of a module named 'Case Study', PPRE masters' students assessed the locally available renewable energy resources and estimated the energy demand for a newly proposed design for the upcoming new Energielabor. This paper presents the first results of these energy demand and resource assessments, along with highlighting the didactical concepts and motivations behind the newly proposed design

Superior skin cancer classification by the combination of human and artificial intelligence

Background: In recent studies, convolutional neural networks (CNNs) outperformed dermatologists in distinguishing dermoscopic images of melanoma and nevi. In these studies, dermatologists and artificial intelligence were considered as opponents. However, the combination of classifiers frequently yields superior results, both in machine learning and among humans. In this study, we investigated the potential benefit of combining human and artificial intelligence for skin cancer classification. Methods: Using 11,444 dermoscopic images, which were divided into five diagnostic categories, novel deep learning techniques were used to train a single CNN. Then, both 112 dermatologists of 13 German university hospitals and the trained CNN independently classified a set of 300 biopsy-verified skin lesions into those five classes. Taking into account the certainty of the decisions, the two independently determined diagnoses were combined to a new classifier with the help of a gradient boosting method. The primary end-point of the study was the correct classification of the images into five designated categories, whereas the secondary end-point was the correct classification of lesions as either benign or malignant (binary classification). Findings: Regarding the multiclass task, the combination of man and machine achieved an accuracy of 82.95%. This was 1.36% higher than the best of the two individual classifiers (81.59% achieved by the CNN). Owing to the class imbalance in the binary problem, sensitivity, but not accuracy, was examined and demonstrated to be superior (89%) to the best individual classifier (CNN with 86.1%). The specificity in the combined classifier decreased from 89.2% to 84%. However, at an equal sensitivity of 89%, the CNN achieved a specificity of only 81.5% Interpretation: Our findings indicate that the combination of human and artificial intelligence achieves superior results over the independent results of both of these systems. (C) 2019 The Author(s). Published by Elsevier Ltd

Survivorship Data in Prostate Cancer: Where Are We and Where Do We Need To Be?

Cancer survivorship was recently identified as a prostate cancer (PCa) research priority by PIONEER, a European network of excellence for big data in PCa. Despite being a research priority, cancer survivorship lacks a clear and agreed definition, and there is a distinct paucity of patient-reported outcome (PRO) data available on the subject. Data collection on cancer survivorship depends on the availability and implementation of (validated) routinely collected patient-reported outcome measures (PROMs). There have been recent advances in the availability of such PROMs. For instance, the European Organisation for Research and Treatment of Cancer Quality of Life Group (EORTC QLG) is developing survivorship questionnaires. This provides an excellent first step in improving the data available on cancer survivorship. However, we propose that an agreed, standardised definition of (prostate) cancer survivorship must first be established. Only then can real-world data on survivorship be collected to strengthen our knowledge base. With more men than ever surviving PCa, this type of research is imperative to ensure that the quality of life of these men is considered as much as their quantity of life. Patient summary: As there are more prostate cancer survivors than ever before, research into cancer survivorship is crucial. We highlight the importance of such research and provide recommendations on how to carry it out. The first step should be establishing agreement on a standardised definition of survivorship. From this, patient-reported outcome measures can then be used to collect important survivorship data