Integrating Knowledge-Driven and Data-Driven Approaches for the Derivation of Clinical Prediction Rules

Kwiatkowska, Mila; Atkins, Anthony; Ayas, Najib; Ryan, C. Frank

doi:10.1109/icmla.2005.41

Cited by 9 publications

(7 citation statements)

References 119 publications

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“…In the method aspect, the data may be collected using different measurements, which leads to varying precision and specifications. Finally, the clinical spectrum bias represented in patient records may show other medical problems apart from the disease [ 61 ]. For instance, Saussele and Pfirrmann [ 62 ] have reported clinical trials in CML.…”

Section: Resultsmentioning

confidence: 99%

Intelligent Techniques Using Molecular Data Analysis in Leukaemia: An Opportunity for Personalized Medicine Support System

Banjar

Adelson

Brown

et al. 2017

BioMed Research International

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The use of intelligent techniques in medicine has brought a ray of hope in terms of treating leukaemia patients. Personalized treatment uses patient's genetic profile to select a mode of treatment. This process makes use of molecular technology and machine learning, to determine the most suitable approach to treating a leukaemia patient. Until now, no reviews have been published from a computational perspective concerning the development of personalized medicine intelligent techniques for leukaemia patients using molecular data analysis. This review studies the published empirical research on personalized medicine in leukaemia and synthesizes findings across studies related to intelligence techniques in leukaemia, with specific attention to particular categories of these studies to help identify opportunities for further research into personalized medicine support systems in chronic myeloid leukaemia. A systematic search was carried out to identify studies using intelligence techniques in leukaemia and to categorize these studies based on leukaemia type and also the task, data source, and purpose of the studies. Most studies used molecular data analysis for personalized medicine, but future advancement for leukaemia patients requires molecular models that use advanced machine-learning methods to automate decision-making in treatment management to deliver supportive medical information to the patient in clinical practice.

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Section: Resultsmentioning

confidence: 99%

Intelligent Techniques Using Molecular Data Analysis in Leukaemia: An Opportunity for Personalized Medicine Support System

Banjar

Adelson

Brown

et al. 2017

BioMed Research International

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“…At present, machine learning that integrates knowledgedriven and data-driven modeling is a frontier research field [43]. Knowledge-driven modeling uses expert knowledge or experience formulas as modeling methods [44]. In ship motion research, Abkowitz model, MMG model and response model, can be regarded as knowledge-driven model.…”

Section: Work Conducted In This Study 1) Methods Employed In This Smentioning

confidence: 99%

White-Black-Box Hybrid Model Identification Based on RM-RF for Ship Maneuvering

2019

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A new system identification scheme based on model reference and random forest (RM-RF), was used to model ship maneuvering. First, the scheme establishes the relationship between a ship and the RM using the similarity rule. Second, a suitable RM was selected from public ship maneuvering models to avoid the tuning process in the empirical Maneuvering Modeling Group (MMG), model. Third, RF creates a relationship to map accelerations between the ship and the RM. Finally, the study case was implemented with fewer free-running model test data. The results show the feasibility of the identification modeling scheme and validated the generalizability of the proposed approach.

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“…Data mining is widely used for knowledge acquisition,and the knowledge discovery process is used as a schema to automatically discover knowledge, which can include the shape of patterns or associations among data features and rules. This process generally includes four steps: problem understanding and data understanding, data pre-processing, model induction, and post-processing [24]. A recent review [25]discussed knowledge discovery in medicine.…”

Section: Clinical Decision Support Systemmentioning

confidence: 99%

“…Data may be collected using different measurements, leading to different precisions and specifications. Finally, the clinical spectrum bias is represented in the patient's record, which may show other medical problems with the disease [24]. For instance, Saussele and Pfirrmann [45] reported clinical trials of chronic myeloid leukemia (CML).…”

Section: Medical Data and Knowledgementioning

confidence: 99%