Process mining in health care

pmhcToday, I have given a lecture on process mining in the health care at the College of Biomedical Engineering & Instrumentation of the Zhejiang University at Hangzhou, China. I concentrated on the application of process mining in a clinical setting with different modalities of data. There are many challenges facing process mining with clinical data and there is a clear need for new algorithms that face this challenge.

Industria Congress 2013 highlights big data

Industria, theindcongres Study Association for Industrial Engineering students in Eindhoven organized its annual congress. Industria Congress 2013 had as its theme “Big Data: big business or big brother?”. At the full-day event with prominent speakers and multiple workshops organized by the industry, the potential and the threats of this new phenomenon were discussed. It became clear that the data-centric view of the business introduces new challenges, while it also transforms the society in a fundamental way. I will talk more about this transformation in the course 1BM56, Business Intelligence.

Computational intelligence approaches to ontology alignment

OASToday, I have given the Information Systems Colloquium for the IS@IEIS and IS@W&I groups of the Eindhoven University of Technology. The presentation covered the application of multi-objective evolutionary methods to certain aspects of the ontology alignment problem in semantic information systems. In the discussion that followed, we have also explored the links of the problem to business process discovery and alignment.

Achieving semantic interoperability is an essential task for all distributed and open knowledge based systems. Currently, the technology recognized for fulfilling this complex task is represented by ontologies. However, the power of ontological representation is reduced by the semantic heterogeneity problem which affects two ontologies when they are characterized by terminological and conceptual discrepancies. The most solid solution to overcome this problem is to perform an ontology alignment process capable of leading two heterogeneous ontologies into a mutual agreement by detecting a set of correspondences between them. Performing this task is an essential step to allow the exchange of information between people, organizations and web applications using ontologies for representing their view of the world. In this presentation, we consider several computational intelligence approaches to ontology alignment. In particular, the use of memetic algorithms, evolutionary approaches and fuzzy set methods are discussed for tackling different aspects of the problem.

Modeling clinical pathways: MSc defense Lonneke Vermeulen

imageLonneke Vermeulen has defended successfully her M.Sc. thesis titled “A Process Modelling Method for Care Pathways”. She developed a methodology for modeling care pathways using BPMN. Lonneke studied Operations Management & Logistics, and her project was a collaboration with Catharina Hospital Eindhoven.

The goal of this research is to design a process modelling method for care pathways (CP) in hospitals, based on the existing literature of the field as well as experiences from practice that is applicable on any kind of pathway. The method focuses on setting the right requirements for the modelling language and tool such that the model can decide on the best possible model for the project starting from the goals (e.g. communication tool, mapping, checklists). Furthermore, special attention is paid on the missing literature aspects of information gathering necessary to model the CP, the relationship between the goals of the model and the necessary granularity levels, and how to set those granularity levels.

Impressive new container terminal rises in Maasvlakte 2

TAPMT_craneoday, I visited the new APM Terminal that is being built in Maasvlakte 2. This will be the first occupant of Maasvlakte 2. Many new logistics concepts are being developed and implemented at this terminal, which will help Rotterdam keep its leading position as the main harbor of Europe. The terminal can handle the largest container ships and can serve two such ships simultaneously!

Anouk Suntjens wins the 2013 VMBI-MIM Future Prize

20131123-082541.jpgAnouk Suntjens, a member of the IS@IEIS Healthcare Research Cluster and a former Operations Management & Logistics (OML) student has won the 2013 Toekomstprijs of VBMI-MIM for her Master’s Thesis. The title of Anouk’s thesis was “Knowledge Translation and Maintenance in Health Care: identification of the requirements for tool support”. Her project was a collaboration with Catharina Hospital Eindhoven. More information about the thesis can be found here.

PhD defense Emiel Caron

Emiel CaronOn 14 November 2013, Emiel Caron has successfully defended his PhD thesis at Erasmus University Rotterdam with the title “Explanation of Expceptional Values in Multi-dimensional Business Databases”. Emiel has studied the question of extending the functionality of multi-dimensional business databases with diagnostic capabilities to support managerial decision-making. He developed formal methods for identifying exceptional values in OLAP approaches and offering automated explanations for these values. The methods Emiel developed will increase the efficiency of business analytics in this age of big data. Congratulations Emiel!

IEEE Forum for Leading Researchers

Today, IEEE has held a forum in Amsterdam for a select group of leading researchers in their fields. This was the third of a series of forums. The other two meetings we held in the United States and in Japan. In the full-day discussions, we tried to understand the current and future status of research processes and tools used in Europe and various parts of the world. Research enterprise is changing significantly at the moment. New ways of publishing, collaborative research in multidisciplinary teams and increasing demand of the society for accountability are fueling these changes. We discussed what the challenges are that come with these changes and how a professional organization like IEEE can help meet these challenges. The outcome of the discussions will soon be shared with the research community.

Financial forecasting for healthcare insurers: MSc defense Sebastiaan van Zelst

Today, Sebastiaan van Zelst defended successfully his M.Sc. thesis titled “Defining a Financial Forecasting Model for Healthcare Insurance Companies: a collaborative Markov chain approach incorporating institutional care pathway traversal”. Sebastiaan studied Business Information Systems and his project was a collaboration with KPMG.

This document concerns an exploratory research towards the application of collaborative Markov chains as a forecasting model within the field of healthcare insurance. The model proposed is based on both predicting care demand and associated institutional pathway traversal. A system of collaborative Markov chains allows the user to jointly model several probabilistic elements that share dependencies. It describes a collection of Markov chains in which the state of a certain chain within the collection influences transition probabilities in other chains within the collection. It allows the use of different types of techniques to estimate forecasting parameters as an input within one model. It entails a modular structure which allows the user to perform case-based analyses. Simulation of simplified proof-of-concept cases has shown accurate predictive behavior. Due to the fact that Markov chains and consequently systems of collaborative Markov chains are probabilistic in nature, simulation of a sufficient number of sampling replication yields results that tend to follow a Normal distribution. The statistical nature of the simulation results lends itself perfectly for consecutive statistical post-processing. Systems of collaborative Markov chains provide in modeling complex probabilistic systems in which several dependencies might exist. Current challenges within the application of systems of collaborative Markov chains involve the complexity in terms of the number of parameters to estimate and associated running times. Additionally the existence of potential “inactive elements” with respect to the field of healthcare insurance introduces additional challenges in parameter estimation of the model.