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This paper proposes a method for construction of classifiers for discharge summaries. First, morphological analysis is applied to a set of summaries and a term matrix is generated. Second, correspond analysis is applied to the classification labels and the term matrixand generates two dimensional coordinates. By measuring thedistance between categories and the assigned points, ranking of key wordswill...
This paper proposes a method for construction of classifiers for discharge summaries. First, morphological analysis is applied to a set of summaries and a term matrix is generated. Second, correspond analysis is applied to the classification labels and the term matrix and generates two dimensional coordinates. By measuring the distance between categories and the assigned points, ranking of key words...
This paper proposes an active mining process for improvement of quality of clinical process by using service logs in a hospital information system. First, datasets of temporal change of the number of orders are extracted from service logs stored in hospital information system. Then, since datsets of temporal change can be viewed as time-series of a statistic, clustering can be applied to the data...
This paper proposes a method which induces a clinical pathway by using sample and attribute clustering of the histories of nursing orders stored in hospital information system. The method consists of the following five steps: first, frequencies of nursing orders are extracted from hospital information system. Second, orders are classified into several groups by using sample clustering. Then, attributes...
In this paper, we attempt to analyze the relationships between the stay time of outpatients and treatment processes they received based on the temporal pattern mining algorithm proposed by Batal et al. We could observe MPTPs (Minimal Predictive Temporal Patterns) of treatment processes containing 'co-occur' relations as well as injections in the classes where the patients spent long time in receiving...
A hospital information system (HIS) was introduced about twenty years ago and all the clinical environment has been dramatically changed [1]–[3]. HIS stores all the histories of clinical activities in a hospital, such as electronic patient records, laboratory data, x-ray photos, and so on. The advantage of HIS is that all the data are input through the network service and they can retrieve from the...
Clinical environment is very complex, and flexible and adaptive service improvement is crucial in maintaining quality of medical care. Thus, incremental update of software service in a hospital information system (HIS) and its evaluation is important. This paper introduces an active mining process for development of a an embedded software in which service logs stored in HIS are used to calculate the...
This paper proposes a method for construction of a clinical pathway based on attribute and sample clustering, called dual clustering. The method consists of the following five steps: first, histories of nursing orders are extracted from hospital information system. Second, orders are classified into several groups by using clustering on the pricipal components (sample clustering). Third, attributes...
This paper presents an attempt to visualize the geographical distribution of outpatients in a hospital as a preliminary step towards the process-dynamics mining. In order to obtain the locations of patients without using devices carried by themselves, we extract clinical action records (e.g. treatments, examinations and injections) from hospital information systems and utilize the locations of information...
This paper overviews problems with healthcare in the coming decade and emerging technologies in healthcare IT. The crucial point is integration of consumer healthcare data and electronic medical records for chronic disease management, where temporal granularity will be one of the most important technical challenges.
This paper proposes granularity-based temporal data mining method which constructs clinical process conducted by nurses. The methods consist of three process. First, data on counting sum of executed orders are extracted from hospital information system with a given temporal granularity. Then, similarity-based methods, such as clustering and multidimensional scaling (MDS) are applied to the data and...
This paper presents a method for mining clinical pathway candidates from order history based on the typical ness index. Firstly, we constitute occurrence and transition frequency matrices of clinical orders based on the all cases. Next, we define the typical ness index of an order sequence based on the occurrence and transition frequencies and compute its value for each case. After that we perform...
This paper presents a typicalness-based cluster analysis scheme for discovering groups of treatment processes that may constitute building blocks for clinical pathways. Experimental results on an otorhinolaryngologic disease dataset demonstrate that the method is capable of producing clusters that reflect differences of treatment processes induced by the differences of operation dates without a priori...
Schedule management of hospitalization is important to maintain or improve the quality of medical care and application of a clinical pathway is one of the important solutions for the management. Although several kinds of deductive methods for construction for a clinical pathway have been proposed, the customization is one of the important problems. This research proposed an inductive approach to support...
Since hospital data include temporal trends of clinical symptoms and medical services, we can discover not only knowledge about temporal evolution of disease, but also one about medical practice from hospital information system, which will lead to data-oriented hospital management. This paper proposes temporal data mining process and applied the method to construction and revision of clinincal pathway...
Since hospital data include temporal trends of clinical symptoms and medical services, we can discover not only knowledge about temporal evolution of disease, but also one about medical practice from hospital information system, which will lead to data-oriented hospital management. This paper proposes temporal data mining process and applied the method to construction and revision of clinincal pathway...
This paper proposes two and three dimensional trajectories mining to analyze the temporal characteristics of hospital services. Trajectories mining method consists of the following two process. First the similarities between temporal trajectories of two or three selected variables are calculated. Second, similarity-based analysis technique such as clustering and multidimensional scaling is applied...
Since hospital data include temporal trends of clinical symptoms and medical services, we can discover not only knowledge about temporal evolution of disease, but also one about medical practice from hospital information system. This paper proposes temporal data mining process and applied the method to capture temporal knowledge about nursing practice. The results show that the reuse of stored data...
Computerization of hospital information enables us to visualize and analyze temporal characteristics of hospital services, which can be viewed as a first step to improve and innovate clinical services. This paper proposes a temporal data mining process which consists of decision tree, clustering, MDS and three-dimensional trajectories mining. The results show that the reuse of stored data will give...
Computerization of hospital information enables us to visualize and analyze temporal characteristics of hospital services, which can be viewed as a first step to improve and innovate clinical services. This paper proposes a temporal data mining process which consists of similarity-based mining such as clustering and MDS. The results show that the reuse of stored data will give a powerful tool to characterize...
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