29 Result(s)
within
Szymon Wilk
Computer Science
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Article
On the joint-effect of class imbalance and overlap: a critical review
Current research on imbalanced data recognises that class imbalance is aggravated by other data intrinsic characteristics, among which class overlap stands out as one of the most harmful. The combination of th...
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Chapter and Conference Paper
Towards an AI Planning-Based Pipeline for the Management of Multimorbid Patients
Treatment of patients with multimorbidity is one of the greatest challenges for clinical decision support. While evidence-based management of specific diseases is supported by clinical practice guidelines, con...
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Chapter and Conference Paper
Comparision of Models Built Using AutoML and Data Fusion
Automated machine learning (AutoML) has made life easier for data analysts or scientists by providing quick insights into data by building machine learning (ML) models. AutoML techniques are applied to vast ar...
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Chapter and Conference Paper
MitPlan 2.0: Enhanced Support for Multi-morbid Patient Management Using Planning
The complexity of patient care is growing due to an ageing population. As chronic illnesses become more common, the incidence of multi-morbidity increases. Generating disease management plans for multi-morbid...
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Chapter and Conference Paper
Catching Patient’s Attention at the Right Time to Help Them Undergo Behavioural Change: Stress Classification Experiment from Blood Volume Pulse
The CAPABLE project aims to improve the wellbeing of cancer patients managed at home via a coaching system recommending personalized evidence-based health behavioral change interventions and supporting patient...
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Chapter and Conference Paper
CAncer PAtients Better Life Experience (CAPABLE) First Proof-of-Concept Demonstration
The CAncer PAtient Better Life Experience (CAPABLE) project combines the most advanced technologies for data and knowledge management with a socio-psychological approach, to develop a coaching system for impro...
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Chapter and Conference Paper
Assessing the Impact of Distance Functions on K-Nearest Neighbours Imputation of Biomedical Datasets
In healthcare domains, dealing with missing data is crucial since absent observations compromise the reliability of decision support models. K-nearest neighbours imputation has proven beneficial since it takes...
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Chapter and Conference Paper
MitPlan: A Planning Approach to Mitigating Concurrently Applied Clinical Practice Guidelines
As the overall population ages, patient complexity and the scope of their care is increasing. Over 60% of the population over 65 years of age suffers from multi-morbidity, which is associated with over two tim...
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Chapter and Conference Paper
Fusion of Clinical Data: A Case Study to Predict the Type of Treatment of Bone Fractures
Clinical data is characterized not only by its constantly increasing volume but also by its diversity. Information collected in clinical information systems such as electronic health records is highly heteroge...
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Chapter and Conference Paper
Using Constraint Logic Programming for the Verification of Customized Decision Models for Clinical Guidelines
Computer-interpretable implementations of clinical guidelines (CIGs) add knowledge that is outside the scope of the original guideline. This knowledge can customize CIGs to patients’ psycho-social context or a...
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Chapter and Conference Paper
MET4: Supporting Workflow Execution for Interdisciplinary Healthcare Teams
This paper describes MET4, a multi-agent system that supports interdisciplinary healthcare teams (IHTs) in executing patient care workflows. Using the concept of capability, the system facilitates the maintena...
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Chapter and Conference Paper
Using First-Order Logic to Represent Clinical Practice Guidelines and to Mitigate Adverse Interactions
Clinical practice guidelines (CPGs) were originally designed to help with evidence-based management of a single disease and such single disease focus has impacted research on CPG computerization. This computer...
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Chapter and Conference Paper
Using Constraint Logic Programming to Implement Iterative Actions and Numerical Measures during Mitigation of Concurrently Applied Clinical Practice Guidelines
There is a pressing need in clinical practice to mitigate (identify and address) adverse interactions that occur when a comorbid patient is managed according to multiple concurrently applied disease-specific c...
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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
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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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 ...
