Katsuhiko Takabayashi

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The hepatitis temporal database collected at Chiba university hospital between 1982--2001 was recently given to challenge the KDD research. The database is large where each patient corresponds to 983 tests represented as sequences of irregular timestamp points with different lengths. This paper presents a temporal abstraction approach to mining knowledge(More)
This paper proposes a novel decision tree for a data set with time-series attributes. Our time-series tree has a value (i.e. a time sequence) of a time-series attribute in its internal node, and splits examples based on dissimilarity between a pair of time sequences. Our method selects, for a split test, a time sequence which exists in data by exhaustive(More)
OBJECTIVE The 2010 American College of Rheumatology/European League Against Rheumatism (ACR/EULAR) classification criteria for rheumatoid arthritis (RA) refer to a possible use of ultrasound "for confirmation of the clinical findings." We undertook this study to determine the optimized definition of ultrasound-detected synovitis for the 2010 ACR/EULAR(More)
BACKGROUND Medicine and biomedical sciences have become data-intensive fields, which, at the same time, enable the application of data-driven approaches and require sophisticated data analysis and data mining methods. Biomedical informatics provides a proper interdisciplinary context to integrate data and knowledge when processing available information,(More)
A machine learning technique called Graph-Based Induction (GBI) efficiently extracts typical patterns from graph-structured data by stepwise pair expansion (pairwise chunking). It is very efficient because of its greedy search. Meanwhile, a decision tree is an effective means of data classification from which rules that are easy to understand can be(More)
OBJECTIVES To examine the architectural differences and similarities of a Japanese and German hospital information system (HIS) in a case study. This cross-cultural comparison, which focuses on structural quality characteristics, offers the chance to get new insights into different HIS architectures, which possibly cannot be obtained by inner-country(More)
Various data mining methods have been developed last few years for hepatitis study using a large temporal and relational database given to the research community. In this work we introduce a novel temporal abstraction method to this study by detecting and exploiting temporal patterns and relations between events in viral hepatitis such as “event A slightly(More)
In this paper, we apply our PrototypeLines to Chronic Hepatitis Data and demonstrate the results so that domain experts can inspect them closely. PrototypeLines represents a method which visualizes irregular multi-dimensional time-series data as a sequence of probabilistic prototypes. It displays summarized information based on a probabilistic mixture model(More)
OBJECTIVE To discuss interdisciplinary research and education in the context of informatics and medicine by commenting on the paper of Kuhn et al. "Informatics and Medicine: From Molecules to Populations". METHOD Inviting an international group of experts in biomedical and health informatics and related disciplines to comment on this paper. RESULTS AND(More)
We analyzed the hepatitis data by Decision Tree GraphBased Induction (DT-GBI), which constructs a decision tree for graphstructured data while simultaneously constructing attributes for classification. An attribute at each node in the decision tree is a discriminative pattern (subgraph) in the input graph, and extracted by Graph-Based Induction (GBI). We(More)