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Article
Implementing an Integrative Multi-agent Clinical Decision Support System with Open Source Software
Clinical decision making is a complex multi-stage process. Decision support can play an important role at each stage of this process. At present, the majority of clinical decision support systems have been foc...
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Chapter and Conference Paper
Discovering the Preferences of Physicians with Regards to Rank-Ordered Medical Documents
The practice of evidence-based medicine involves consulting documents from repositories such as Scopus, PubMed, or the Cochrane Library. The most common approach for presenting retrieved documents is in the fo...
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Chapter and Conference Paper
Indexing and Retrieval of Medical Resources for a Telemedical Platform
In this paper we present an indexing and retrieval service for a telemedical platform. While the service has been deployed in the Wielkopolska Center of Telemedicine (WCT) – a platform to facilitate teleconsul...
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Chapter and Conference Paper
A Constraint Logic Programming Approach to Identifying Inconsistencies in Clinical Practice Guidelines for Patients with Comorbidity
This paper describes a novel methodological approach to identifying inconsistencies when concurrently using multiple clinical practice guidelines. We discuss how to construct a formal guideline model using Con...
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Chapter and Conference Paper
Classifying Severely Imbalanced Data
Learning from data with severe class imbalance is difficult. Established solutions include: under-sampling, adjusting classification threshold, and using an ensemble. We examine the performance of combining th...
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Article
A Tree-Based Decision Model to Support Prediction of the Severity of Asthma Exacerbations in Children
This paper describes the development of a tree-based decision model to predict the severity of pediatric asthma exacerbations in the emergency department (ED) at 2 h following triage. The model was constructed...
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Chapter and Conference Paper
Learning from Imbalanced Data in Presence of Noisy and Borderline Examples
In this paper we studied re-sampling methods for learning classifiers from imbalanced data. We carried out a series of experiments on artificial data sets to explore the impact of noisy and borderline examples...
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Chapter and Conference Paper
Integrating Selective Pre-processing of Imbalanced Data with Ivotes Ensemble
In the paper we present a new framework for improving classifiers learned from imbalanced data. This framework integrates the SPIDER method for selective data pre-processing with the Ivotes ensemble. The goal ...
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Chapter and Conference Paper
Experienced Physicians and Automatic Generation of Decision Rules from Clinical Data
Clinical Decision Support Systems embed data-driven decision models designed to represent clinical acumen of an experienced physician. We argue that eliminating physicians’ diagnostic biases from data improves...
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Chapter
Extending Rule-Based Classifiers to Improve Recognition of Imbalanced Classes
Knowledge discovery in general, and data mining in particular, have received a growing interest both from research and industry in recent years. Its main aim is to look for previously unknown relationships or ...
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Chapter and Conference Paper
Selective Pre-processing of Imbalanced Data for Improving Classification Performance
In this paper we discuss problems of constructing classifiers from imbalanced data. We describe a new approach to selective pre-processing of imbalanced data which combines local over-sampling of the minority ...
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Chapter and Conference Paper
A Concept-Based Framework for Retrieving Evidence to Support Emergency Physician Decision Making at the Point of Care
The goal of evidence-based medicine is to uniformly apply evidence gained from scientific research to aspects of clinical practice. In order to achieve this goal, new applications that integrate increasingly d...
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Chapter and Conference Paper
Using Secondary Knowledge to Support Decision Tree Classification of Retrospective Clinical Data
Retrospective clinical data presents many challenges for data mining and machine learning. The transcription of patient records from paper charts and subsequent manipulation of data often results in high volum...
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Article
Using a Bayesian belief network model to categorize length of stay for radical prostatectomy patients
A clinical pathway implements best medical practices and represents sequencing and timing of interventions by clinicians for a particular clinical presentation. We used a Bayesian belief network (BBN) to model...
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Chapter and Conference Paper
Develo** a Decision Model for Asthma Exacerbations: Combining Rough Sets and Expert-Driven Selection of Clinical Attributes
The paper describes the development of a clinical decision model to help Emergency Department physicians assess the severity of pediatric asthma exacerbations. The model should support an early identification ...
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Article
A Comparison of Two Approaches to Data Mining from Imbalanced Data
Our objective is a comparison of two data mining approaches to dealing with imbalanced data sets. The first approach is based on saving the original rule set, induced by the LEM2 (Learning from Example Module)...
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Chapter and Conference Paper
Mining Clinical Data: Selecting Decision Support Algorithm for the MET-AP System
We have developed an algorithm for triaging acute pediatric abdominal pain in the Emergency Department using the discovery-driven approach. This algorithm is embedded into the MET-AP (Mobile Emergency Triage –...
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Chapter and Conference Paper
Rough Set Methodology in Clinical Practice: Controlled Hospital Trial of the MET System
Acute abdominal pain in childhood is a common but diagnostically challenging problem facing Emergency Department personnel. Experienced physicians use a combination of key clinical attributes to assess and tri...
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Chapter and Conference Paper
A Comparison of Two Approaches to Data Mining from Imbalanced Data
Our objective is a comparison of two data mining approaches to dealing with imbalanced data sets. The first approach is based on saving the original rule set, induced by the LEM2 algorithm, and changing the ru...
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Chapter and Conference Paper
Identifying Important Attributes for the Siberian Forests Management Using Rough Sets Analysis
This presentation discusses identification of attributes that are considered essential for a development of sustainable forest management practices in the Siberian forests. This goal is accomplished through an...
