Case-Based Reasoning in the Health Sciences: Foundations and Research Directions

@inproceedings{Bichindaritz2010CaseBasedRI,
  title={Case-Based Reasoning in the Health Sciences: Foundations and Research Directions},
  author={Isabelle Bichindaritz and Cynthia R. Marling},
  year={2010}
}
Case-based reasoning (CBR) is an Artificial Intelligence (AI) approach with broad applicability to building intelligent systems in health sciences domains. It represents knowledge in the form of exemplary past experiences, or cases. It is especially well suited to health sciences domains, where experience plays a major role in acquiring knowledge and skill, and where case histories inform current practice. This chapter provides a broad overview of CBR in the Health Sciences, including its… 
Synergistic case-based reasoning in medical domains
Using Automated Feature Selection for Building Case-Based Reasoning Systems: An Example from Patient-Reported Outcome Measurements
TLDR
A two-fold approach employed on the dataset for feature selection that combines statistical strength with data-driven knowledge modelling in CBR and compares it with permutation feature selection using XGBoost regressor is presented.
CWDM: A Case-based Diabetes Management Web System
TLDR
A case-based lifecycle for Diabetes Management (DM) consisting of case- based symptoms,case-based diagnosis, case- Based prognosis, cases-based treatment, and case-Based care is proposed with CBR as an intelligent intermediary.
Learning Case-Based Reasoning Solutions by Association Rules Approach
TLDR
This work aims to propose an approach that combines Association Rules and CBR to improve searching solution for similar cases and test the approach by using real-life datasets.
A Temporal Case-Based Reasoning Platform Relying on a Fuzzy Vector Spaces Object-Oriented Model and a Method to Design Knowledge Bases and Decision Support Systems in Multiple Domains
TLDR
It is shown how temporal case-based reasoning can use distances between temporal fuzzy vector functions to compare these knowledge objects’ evolution and the current limitations of the proposed model, its future perspectives and possible platform enhancements.
Research on fault diagnosis of aeroengine endoscopic detection based on CBR and RBR
TLDR
The combination of rule- based reasoning (RBR) and case-based reasoning (CBR) is used to build an expert system for the endoscopic detection of aero-engines, which forms the expert system knowledge base, which is stored in the database.
A Case-Based Retrieval System Using Natural Language Processing and Population-Based Visualization
TLDR
A case-based retrieval framework is presented that incorporates an extraction tool to identify concepts from clinical reports, a disease model to capture necessary context for interpreting extracted concepts, and a model-driven visualization to facilitate querying and interpretation of the results.
MED-HYREC: A Recommendation System for Medical Domain
TLDR
Case-based reasoning, which is a subfield of artificial intelligence, is used and an algorithm is developed for this purpose to develop a system that can accept the information related to the symptoms, diseases, timelines, medical procedures, and medications experienced by various people.
Clustering to Enhance Case-Based Reasoning
TLDR
An approach to improve CBR processing mainly in its retrieval task using CBR and clustering to reduce the search space in the retrieval step and provide an intelligent strategy that enables decision makers to have the best decision aid.
...
...

References

SHOWING 1-10 OF 89 REFERENCES
Case-based reasoning in the health sciences: What's next?
Case-Based Reasoning in the Health Sciences: Why It Matters for the Health Sciences and for CBR
TLDR
An interesting question to study is whether CBR could become one day as fundamental to the health sciences as statistics is today, which broadens the health Sciences challenge to a universal scope.
INTRODUCTION TO THE SPECIAL ISSUE ON CASE‐BASED REASONING IN THE HEALTH SCIENCES
TLDR
Nine high-quality papers introduced here represent the research and experience of twenty-two authors working in eight different countries on a wide range of problems and projects and illustrate some of the major trends of current research in CBR in the health sciences.
Exploring new roles for case-based reasoning in heterogeneous AI systems for medical decision support
  • S. Montani
  • Computer Science
    Applied Intelligence
  • 2007
TLDR
A modular architecture is proposed, in which several AI methodologies cooperate, to provide decision support, and CBR, originally conceived as a well suited reasoning paradigm for medical applications, can extend its original roles, and cover a set of additional tasks.
CASE‐BASED REASONING AND KNOWLEDGE DISCOVERY IN MEDICAL APPLICATIONS WITH TIME SERIES
TLDR
The role and integration of knowledge discovery (KD) in case‐based reasoning (CBR) systems is discussed and it is shown that the approach is able to identify key sequences that would improve the classification ability and may spawn clinical research to explain the co‐occurrence between certain sequences and classes.
Case-based reasoning in the health sciences
Cased-Based Reasoning for medical knowledge-based systems
Case-Based Reasoning in CARE-PARTNER: Gathering Evidence for Evidence-Based Medical Practice
TLDR
The role of case-based reasoning is presented in this paper as the collection of evidence for evidence-based medical practice and enhances the system by conferring an ability to learn from experience, and thus improve results over time.
Using Experience in Clinical Problem Solving: Introduction and Framework
TLDR
A model of experience's role in commonsense problem solving is developed and a model of clinical reasoning that incorporates experience is proposed, including reasoning processes that make use of previous experience and a well-developed memory model that allows retrieval of individual experiences from memory as needed.
Prototypical Cases for Knowledge Maintenance in Biomedical CBR
TLDR
Knowledge maintenance is presented as another role that these prototypical cases can play in biomedical CBR systems, among which to organize and structure the memory and to serve as bootstrapping a CBR system memory when real cases are not available.
...
...