LNCS 5943

This book constitutes the thoroughly refereed papers from the BPM 2013 Joint Workshop on Process-Oriented Information Systems and Knowledge Representation in Health Care, KR4HC 2013/ProHealth 2013, held in Murcia, Spain, in June 2013. The 10 revised full papers presented together with 1 keynote paper were carefully reviewed and selected from 19 submissions. The papers are organized in topical sections on semantic interoperability in health care; modeling clinical guidelines; knowledge-based techniques for handling clinical data; and context aware services and guidance.

This book constitutes thoroughly refereed revised selected papers from the BPM 2012 Joint Workshop on Process-Oriented Information Systems and Knowledge Representation in Health Care, ProHealth 2012/KR4HC 2012, held in Tallinn, Estonia, in September 2012. The 9 papers presented were carefully reviewed and selected from 19 submissions. In addition the book contains 1 keynote paper and 2 invited contributions. The papers are organized in topical sections named: guidelines and summarization; archetypes and cooperation; and process mining and temporal analysis.

This book constitutes the refereed proceedings of two workshops held at the International Conference on Health – Exploring Complexity and Medical Informatics Europe, HEC 2016, held in Munich, Germany, in September 2016: the 8th International Workshop on Knowledge Representation for Health Care, KR4HC 2016, and the 9th International Workshop on Process-oriented Information Systems in Healthcare, ProHealth 2016. The 8 revised full papers were carefully reviewed and selected from 12 submissions. The papers are organized in topical sections on ontologies in health care; clinical quality, evaluation, and simulation; computer guidelines engineering and usage; and comorbidity and clinical process management.

This book constitutes the thoroughly refereed post-workshop proceedings of two workshops held at the International Conference on Artificial Intelligence in Medicine, AIME 2015, held in Pavia, Italy, in June 2015: the 7th International Workshop on Knowledge Representation for Health Care, KR4HC 2015, and the 8th International Workshop on Process-oriented Information Systems in Healthcare, ProHealth 2015. The 10 revised full papers were carefully reviewed and selected from 26 submissions. The papers are organized in topical sections on knowledge-driven health IT and simulation, clinical guideline and clinical pathway support, mobile process and decision support, and health information systems and clinical data.

This book constitutes the refereed proceedings of the Third International KR4HC 2011 workshop held in conjunction with the 13th Conference on Artificial Intelligence in medicine, AIME 2011, in Bled, Slovenia, in July 2011. The 11 extended papers presented together with 1 invited paper were carefully reviewed and selected from 22 submissions. The papers cover topics like health care knowledge sharing; health process; clinical practice guidelines; and patient records, ontologies, medical costs, and clinical trials.

This book constitutes the proceedings of the KR4HC 2010 workshop held at ECAI in Lisbon, Portugal, in August 2010. The 11 extended papers presented were carefully reviewed and selected from 19 submissions. The papers cover topics like ontologies, patient data, records, and guidelines, and clinical practice guidelines.

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data

Medicine and health care are currently faced with a significant rise in their complexity. This is partly due to the progress made during the past three decades in the fundamental biological understanding of the causes of health and disease at the molecular, (sub)cellular, and organ level. Since the end of the 1970s, when knowledge representation and reasoning in the biomedical field became a separate area of research, huge progress has been made in the development of methods and tools that are finally able to impact on the way medicine is being practiced. Even though there are huge differences in the techniques and methods used by biomedical researchers, there is now an increasing tendency to share research results in terms of formal knowledge representation methods, such as ontologies, statistical models, network models, and mathematical models. As there is an urgent need for health-care professionals to make better decisions, computer-based support using this knowledge is now becoming increasingly important. It may also be the only way to integrate research results from the different parts of the spectrum of biomedical and clinical research. The aim of this book is to shed light on developments in knowledge representation at different levels of biomedical application, ranging from human biology to clinical guidelines, and using different techniques, from probability theory and differential equations to logic. The book starts with two introductory chapters followed by 18 contributions organized in the following topical sections: diagnosis of disease; monitoring of health and disease and conformance; assessment of health and personalization; prediction and prognosis of health and disease; treatment of disease; and recommendations.

What are the possibilities for process mining in hospitals? In this book the authors provide an answer to this question by presenting a healthcare reference model that outlines all the different classes of data that are potentially available for process mining in healthcare and the relationships between them. Subsequently, based on this reference model, they explain the application opportunities for process mining in this domain and discuss the various kinds of analyses that can be performed. They focus on organizational healthcare processes rather than medical treatment processes. The combination of event data and process mining techniques allows them to analyze the operational processes within a hospital based on facts, thus providing a solid basis for managing and improving processes within hospitals. To this end, they also explicitly elaborate on data quality issues that are relevant for the data aspects of the healthcare reference model. This book mainly targets advanced professionals involved in areas related to business process management, business intelligence, data mining, and business process redesign for healthcare systems as well as graduate students specializing in healthcare information systems and process analysis.