Process Mining in Healthcare
Process Mining in Healthcare

Author: Ronny S. Mans

Publisher: Springer

Published: 2015-03-12

Total Pages: 99

ISBN-13: 3319160710

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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.

Process Mining
Process Mining

Author: Wil M. P. van der Aalst

Publisher: Springer

Published: 2016-04-15

Total Pages: 477

ISBN-13: 3662498510

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This is the second edition of Wil van der Aalst’s seminal book on process mining, which now discusses the field also in the broader context of data science and big data approaches. It includes several additions and updates, e.g. on inductive mining techniques, the notion of alignments, a considerably expanded section on software tools and a completely new chapter of process mining in the large. It is self-contained, while at the same time covering the entire process-mining spectrum from process discovery to predictive analytics. After a general introduction to data science and process mining in Part I, Part II provides the basics of business process modeling and data mining necessary to understand the remainder of the book. Next, Part III focuses on process discovery as the most important process mining task, while Part IV moves beyond discovering the control flow of processes, highlighting conformance checking, and organizational and time perspectives. Part V offers a guide to successfully applying process mining in practice, including an introduction to the widely used open-source tool ProM and several commercial products. Lastly, Part VI takes a step back, reflecting on the material presented and the key open challenges. Overall, this book provides a comprehensive overview of the state of the art in process mining. It is intended for business process analysts, business consultants, process managers, graduate students, and BPM researchers.

Process Mining in Action
Process Mining in Action

Author: Lars Reinkemeyer

Publisher: Springer Nature

Published: 2020-03-14

Total Pages: 216

ISBN-13: 3030401723

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This book describes process mining use cases and business impact along the value chain, from corporate to local applications, representing the state of the art in domain know-how. Providing a set of industrial case studies and best practices, it complements academic publications on the topic. Further the book reveals the challenges and failures in order to offer readers practical insights and guidance on how to avoid the pitfalls and ensure successful operational deployment. The book is divided into three parts: Part I provides an introduction to the topic from fundamental principles to key success factors, and an overview of operational use cases. As a holistic description of process mining in a business environment, this part is particularly useful for readers not yet familiar with the topic. Part II presents detailed use cases written by contributors from a variety of functions and industries. Lastly, Part III provides a brief overview of the future of process mining, both from academic and operational perspectives. Based on a solid academic foundation, process mining has received increasing interest from operational businesses, with many companies already reaping the benefits. As the first book to present an overview of successful industrial applications, it is of particular interest to professionals who want to learn more about the possibilities and opportunities this new technology offers. It is also a valuable resource for researchers looking for empirical results when considering requirements for enhancements and further developments.

Interactive Process Mining in Healthcare
Interactive Process Mining in Healthcare

Author: Carlos Fernandez-Llatas

Publisher: Springer

Published: 2021-10-29

Total Pages: 306

ISBN-13: 9783030539955

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This book provides a practically applicable guide to the methodologies and technologies for the application of interactive process mining paradigm. Case studies are presented where this paradigm has been successfully applied in emergency medicine, surgery processes, human behavior modelling, strokes and outpatients’ services, enabling the reader to develop a deep understanding of how to apply process mining technologies in healthcare to support them in inferring new knowledge from past actions, and providing accurate and personalized knowledge to improve their future clinical decision-making. Interactive Process Mining in Healthcare comprehensively covers how machine learning algorithms can be utilized to create real scientific evidence to improve daily healthcare protocols, and is a valuable resource for a variety of health professionals seeking to develop new methods to improve their clinical decision-making.

Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques

Author: Jiawei Han

Publisher: Elsevier

Published: 2011-06-09

Total Pages: 740

ISBN-13: 0123814804

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Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. - Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects - Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields - Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data

Process Management
Process Management

Author: Jörg Becker

Publisher: Springer Science & Business Media

Published: 2013-06-05

Total Pages: 347

ISBN-13: 354024798X

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Process Management is a compendium for modern design of process-oriented companies. A hands-on approach introducing, realizing and continually administering process management is presented with a thoroughly critical reflection of the necessary activities regarding the state of the art of organization theory and information management. This is done by following individual stages of a process model which has already successfully proved in practice. The progress of the project is described by a continuous case study which is the process management project of a modern service company. The included recommendations are summarized in a series of checklists for each stage of the project.

Mining of Massive Datasets
Mining of Massive Datasets

Author: Jure Leskovec

Publisher: Cambridge University Press

Published: 2014-11-13

Total Pages: 480

ISBN-13: 1107077230

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Now in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets.

Business Process Management Workshops
Business Process Management Workshops

Author: Florian Daniel

Publisher: Springer Science & Business Media

Published: 2012-01-25

Total Pages: 534

ISBN-13: 3642281079

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LNBIP 99 and LNBIP 100 together constitute the thoroughly refereed proceedings of 12 international workshops held in Clermont-Ferrand, France, in conjunction with the 9th International Conference on Business Process Management, BPM 2011, in August 2011. The 12 workshops focused on Business Process Design (BPD 2011), Business Process Intelligence (BPI 2011), Business Process Management and Social Software (BPMS2 2011), Cross-Enterprise Collaboration (CEC 2011), Empirical Research in Business Process Management (ER-BPM 2011), Event-Driven Business Process Management (edBPM 2011), Process Model Collections (PMC 2011), Process-Aware Logistics Systems (PALS 2011), Process-Oriented Systems in Healthcare (ProHealth 2011), Reuse in Business Process Management (rBPM 2011), Traceability and Compliance of Semi-Structured Processes (TC4SP 2011), and Workflow Security Audit and Certification (WfSAC 2011). In addition, the proceedings also include the Process Mining Manifesto (as an Open Access Paper), which has been jointly developed by more than 70 scientists, consultants, software vendors, and end-users. LNBIP 99 contains the revised and extended papers from BPD 2011, BPI 2011 (including the Process Mining Manifesto), BPMS2 2011, CEC 2011, ER-BPM 2011, and edBPM 2011.

Process Mining Workshops
Process Mining Workshops

Author: Sander Leemans

Publisher: Springer Nature

Published: 2021-03-30

Total Pages: 400

ISBN-13: 3030726932

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This book constitutes revised selected papers from the International Workshops held at the Second International Conference on Process Mining, ICPM 2020, which took place during October 4-9, 2020. The conference was planned to take place in Padua, Italy, but had to be held online due to the COVID-19 pandemic. The conference focuses on the area of process mining research and practice, including theory, algorithmic challenges, and applications. The co-located workshops provided a forum for novel research ideas. The 29 papers included in this volume were carefully reviewed and selected from 59 submissions. They stem from the following workshops: 1st International Workshop on Event Data and Behavioral Analytics (EDBA) 1st International Workshop on Leveraging Machine Learning in Process Mining (ML4PM) 1st International Workshop on Streaming Analytics for Process Mining (SA4PM'20) 5th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI) 3rd International Workshop on Process-Oriented Data Science for Healthcare (PODS4H) 1st International Workshop on Trust and Privacy in Process Analytics (TPPA)

Business Process Management Forum
Business Process Management Forum

Author: Claudio Di Ciccio

Publisher: Springer Nature

Published: 2022-09-06

Total Pages: 237

ISBN-13: 3031161718

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This book constitutes the proceedings of the BPM Forum held at the 20th International Conference on Business Process Management, BPM 2022, which took place in Münster, Germany, in September 2022. The BPM Forum hosts innovative research which has a high potential of stimulating discussions. The papers selected for the forum are expected to showcase fresh ideas from exciting and emerging topics in BPM, even if they are not yet as mature as the regular papers at the conference. The 13 full papers included in this volume were carefully reviewed and selected from 98 submissions. The papers were organized in topical sections named: modeling and design; process mining; and predictive process monitoring.