الصفحة 1
الصفحة 1
Modern hospice design : The architecture of palliative and social care
Takes cognisance of the new conditions of social care in the 21st century, principally in the UK, Europe and North America. It does so with regard to the development of new building types, but also in response to new philosophies of palliative care and the status of the elderly and the dying. At its core is a public discussion of a philosophy of design for providing care for the elderly and the vulnerable, taking the importance of architectural aesthetics, the use of quality materials, the porousness of design to the wider world, and the integration of indoor and outdoor spaces as part of the overall care environment.
Innovations in healthcare and outcome measurement : New approaches for a healthy lifestyle
Aims to bring up-to-date new ideas, opinions, development, and critical issues in healthcare and personalized medicine. We are interested in relevant articles covering a broad range of topics, such as: Advances in medical devices, Digitalization and data-driven technologies, AI and algorithm-based drug development (molecule building, enhancement, clinical trials), Diagnostic imaging, Personalized medicine, Nutrition, Oral health care, Healthcare management in certain diseases and population groups, Regulatory developments, Data management, Digital healthcare.
Health services marketing : A practitioner's guide
Health Services Marketing: A Practitioner’s Guide clearly and succinctly explains the range of marketing activities and techniques, from promotions to pricing, so any health professional can learn to navigate this bewildering but increasingly important aspect of healthcare.
Machine learning in healthcare : Fundamentals and recent applications
Discusses how to build various ML algorithms and how they can be applied to improve healthcare systems. Healthcare applications of AI are innumerable: medical data analysis, early detection and diagnosis of disease, providing objective-based evidence to reduce human errors, curtailing inter- and intra-observer errors, risk identification and interventions for healthcare management, real-time health monitoring, assisting clinicians and patients for selecting appropriate medications, and evaluating drug responses. Extensive demonstrations and discussion on the various principles of machine learning and its application in healthcare is provided, along with solved examples and exercises.
Machine learning and deep learning in medical data analytics and healthcare applications
Introduces and explores a variety of schemes designed to empower, enhance, and represent multi-institutional and multi-disciplinary machine learning (ML) and deep learning (DL) research in healthcare paradigms. Serving as a unique compendium of existing and emerging ML/DL paradigms for the healthcare sector, this book demonstrates the depth, breadth, complexity, and diversity of this multi-disciplinary area. It provides a comprehensive overview of ML/DL algorithms and explores the related use cases in enterprises such as computer-aided medical diagnostics, drug discovery and development, medical imaging, automation, robotic surgery, electronic smart records creation, outbreak prediction, medical image analysis, and radiation treatments.
Community Health Cares O-Process for Evaluation : A Participatory Approach for Increasing Sustainability
Community Health Care’s O-Process for Evaluation offers step-by-step assistance in achieving these goals, from determining areas for assessment to disseminating the results. The steps can be conducted in-house or adapted for use with outsiders, laying a solid foundation for a cycle of continuous evaluation and continued improvement for long-term sustainability.
Artificial Intelligence Applications for Health Care
Covers topics on health care and artificial intelligence. Data sets related to biomedical signals (ECG, EEG, EMG) and images (X-rays, MRI, CT) are explored, analyzed, and processed through different computation intelligence methods. Applications of computational intelligence techniques like artificial and deep neural networks, swarm optimization, expert systems, decision support systems, clustering, and classification techniques on medial datasets are explained. Survey of medical signals, medial images, and computation intelligence methods are also provided.
14th Nordic-Baltic conference on biomedical engineering and medical physics : NBC 2008 16–20 June 2008 Riga, Latvia
The topics covered by the Conference Proceedings include: Biomaterials and Tissue Engineering; Biomechanics, Artificial Organs, Implants and Rehabilitation; Biomedical Instrumentation and Measurements, Biosensors and Transducers; Biomedical Optics and Lasers; Healthcare Management, Education and Training; Information Technology to Health; Medical Imaging, Telemedicine and E-Health; Medical Physics; Micro and Nanoobjects, Nanostructured Systems, Biophysics
