Export Citations
Save this search
Please login to be able to save your searches and receive alerts for new content matching your search criteria.
- research-articleFebruary 2025
A novel case-based reasoning system for explainable lung cancer diagnosis
Computers in Biology and Medicine (CBIM), Volume 185, Issue Chttps://doi.org/10.1016/j.compbiomed.2024.109547AbstractLung cancer is a leading cause of cancer death worldwide. The survival rate is generally higher when this disease is detected in its early stages. Advances in artificial intelligence (AI) have enabled the development of decision support systems ...
Highlights- An explainable case-based reasoning (XCBR) approach is proposed.
- The proposed XCBR is enhanced by naïve Bayes and MLP classifiers.
- HHO algorithm enhances model practicality through feature selection and weighting.
- Shapley ...
- research-articleDecember 2024
GS-CBR-KBQA: Graph-structured case-based reasoning for knowledge base question answering
Expert Systems with Applications: An International Journal (EXWA), Volume 257, Issue Chttps://doi.org/10.1016/j.eswa.2024.125090AbstractKnowledge Base Question Answering (KBQA) task is an important research direction in natural language processing. Due to the flexibility and ambiguity of natural language, users’ questions often have more complex query types and richer semantic ...
- research-articleNovember 2024
Patient privacy protection: Generating available medical treatment plans based on federated learning and CBR
AbstractAlthough the favorable impact of sharing electronic medical records (EMRs) with other hospitals on improving clinical decision-making efficiency is widely acknowledged, the actual implementation of EMR sharing has been limited to some extent ...
- research-articleOctober 2024
iSee: A case-based reasoning platform for the design of explanation experiences
- Marta Caro-Martínez,
- Juan A. Recio-García,
- Belén Díaz-Agudo,
- Jesus M. Darias,
- Nirmalie Wiratunga,
- Kyle Martin,
- Anjana Wijekoon,
- Ikechukwu Nkisi-Orji,
- David Corsar,
- Preeja Pradeep,
- Derek Bridge,
- Anne Liret
AbstractExplainable Artificial Intelligence (XAI) is an emerging field within Artificial Intelligence (AI) that has provided many methods that enable humans to understand and interpret the outcomes of AI systems. However, deciding on the best explanation ...
Graphical abstractDisplay Omitted
- research-articleSeptember 2024
A new hybrid reasoning model based on rules, cases and processes: application to care of individuals facing autism spectrum disorders
Knowledge and Information Systems (KAIS), Volume 67, Issue 1Pages 371–401https://doi.org/10.1007/s10115-024-02228-xAbstractCombining Rule-based reasoning and Case-based reasoning has been widely used, exhibiting quite successful results, since they have complementary capabilities. A system that can utilize both approaches could potentially take advantage of the ...
-
- research-articleSeptember 2024
A two-stage case-based reasoning driven classification paradigm for financial distress prediction with missing and imbalanced data
Expert Systems with Applications: An International Journal (EXWA), Volume 249, Issue PChttps://doi.org/10.1016/j.eswa.2024.123745AbstractFinancial distress prediction often accompanies missing sample feature data and imbalanced normal and abnormal samples. To solve missing and imbalanced data that have significant negative impacts on the financial distress prediction model, a two-...
- ArticleJuly 2024
A Case-Based Reasoning and Explaining Model for Temporal Point Process
Case-Based Reasoning Research and DevelopmentPages 127–142https://doi.org/10.1007/978-3-031-63646-2_9AbstractEvent sequence data widely exists in real life, where each event can be typically represented as a tuple, event type and occurrence time. Combined with deep learning, temporal point process (TPP) has gained a lot of success for event forecasting. ...
- research-articleJuly 2024
An improved case-based reasoning approach for sustainable rural development applied to strategic responses
Engineering Applications of Artificial Intelligence (EAAI), Volume 133, Issue PDhttps://doi.org/10.1016/j.engappai.2024.108316AbstractSustainable development has become a worldwide consensus in recent years. It has become increasingly important to study how to make effective management decisions in rural areas to achieve sustainable development. In this paper, we develop a new ...
Highlights- A CBR-based approach for sustainable rural development strategy response is innovatively developed.
- Using ontology method to build a sustainable rural development domain model.
- A BDCI-based case retrieval algorithm is proposed to ...
- research-articleJune 2024
A Recommender System for Educational Planning
Cybernetics and Information Technologies (CYBAIT), Volume 24, Issue 2Pages 67–85https://doi.org/10.2478/cait-2024-0016AbstractKnowledge-based recommender systems have always had their privileged place among all Decision Support Systems (DSS), given their advantage on several points over other techniques. Our paper presents a framework implementing a hybrid form of Rule-...
- research-articleApril 2024
A recommendation model of rice fertilization using knowledge graph and case-based reasoning
Computers and Electronics in Agriculture (COEA), Volume 219, Issue Chttps://doi.org/10.1016/j.compag.2024.108751Highlights- Establishing a novel rice fertilization recommendation model.
- Employing a combination of knowledge graph and case-based reasoning.
- Achieving high-precision fertilization plans with limited real-time field data.
- Improving the ...
Rice fertilization management plays an important role in rice yield and quality; however, making automatic fertilization plans according to the rice life cycle is difficult. This study proposes a rice fertilization recommendation model using a ...
- research-articleApril 2024
How to select plan in emergency decision-making? A two-stage method with case-based reasoning and prospect theory
AbstractEmergency events characterized by high uncertainty and complexity bring tremendous pressure and challenges to our society. Emergency decision-making (EDM) is an effective way to mitigate the losses caused by emergency events. The generation of ...
Highlights- Introducing a heterogeneous multi-attribute information to describe emergency event and calculate similarity.
- Developing an adaptive reaching process model with hybrid strategies to retrieve dynamically similar events.
- Considered ...
- research-articleMarch 2024
Case-based selection of explanation methods for neural network image classifiers
- Humberto Parejas-Llanovarced,
- Marta Caro-Martínez,
- Mauricio G. Orozco-del-Castillo,
- Juan A. Recio-García
AbstractDeep learning is especially remarkable in terms of image classification. However, the outcomes of models are not explainable to users due to their complex nature, having an impact on the users’ trust in the provided classifications. To solve this ...
Graphical abstractDisplay Omitted
- research-articleMarch 2024
A decision-making system based on case-based reasoning for predicting stroke rehabilitation demands in heterogeneous information environment
AbstractRecently, the increasing number of stroke survivors has created a greater demand for rehabilitation services. How to predict rehabilitation demands is important for policy makers in various countries. The demand prediction is essentially a multi-...
Highlights- The model can be used to handle heterogeneous information expressed by various formats of data in stroke rehabilitation.
- A deviation minimization optimization model was proposed.
- The subjective assessment matrix is constructed ...
- research-articleSeptember 2023
A novel breast cancer detection architecture based on a CNN-CBR system for mammogram classification
Computers in Biology and Medicine (CBIM), Volume 163, Issue Chttps://doi.org/10.1016/j.compbiomed.2023.107133AbstractThis paper presents a novel framework for breast cancer detection using mammogram images. The proposed solution aims to output an explainable classification from a mammogram image. The classification approach uses a Case-Based Reasoning system (...
Highlights- Conduct data cleansing on the CBIS-DDSM dataset by using a ResNext model.
- Combine a SE-ResNet for segmentation and a CBR for an interpretable classification.
- Propose a similarity measure for the CBR Retrieve module.
- Outpass the ...
- ArticleSeptember 2023
Leveraging both Successes and Failures in Case-Based Reasoning for Optimal Solutions
AbstractUsually, existing works on adaptation in case-based reasoning assume that the case base holds only successful cases, i.e., cases having solutions believed to be appropriate for the corresponding problems. However, in practice, the case base could ...
- ArticleJuly 2023
Learning from Successes and Failures: An Exploration of a Case-Based Reasoning Technique
Advances and Trends in Artificial Intelligence. Theory and ApplicationsPages 74–87https://doi.org/10.1007/978-3-031-36819-6_7AbstractUsually, existing works on adaptation in case-based reasoning assume that the case base holds only successful cases, i.e., cases having solutions believed to be appropriate for the corresponding problems. However, in practice, the case base could ...
- ArticleJuly 2023
Reducing Reliance on Domain Knowledge in Case-Based Reasoning
Advances and Trends in Artificial Intelligence. Theory and ApplicationsPages 3–13https://doi.org/10.1007/978-3-031-36819-6_1AbstractCase-based reasoning is an intuitive approach to problem-solving in artificial intelligence that involves reusing existing experience, including solutions to problems or mechanisms to derive them. However, current Case-based reasoning systems ...
- ArticleJuly 2023
Cases Are King: A User Study of Case Presentation to Explain CBR Decisions
Case-Based Reasoning Research and DevelopmentPages 153–168https://doi.org/10.1007/978-3-031-40177-0_10AbstractFrom the early days of case-based reasoning research, the ability of CBR systems to explain their decisions in terms of past cases has been seen as an important advantage. However, there have been few studies on the factors affecting the ...
- research-articleApril 2023
Robust and explainable identification of logical fallacies in natural language arguments
- Zhivar Sourati,
- Vishnu Priya Prasanna Venkatesh,
- Darshan Deshpande,
- Himanshu Rawlani,
- Filip Ilievski,
- Hông-Ân Sandlin,
- Alain Mermoud
AbstractThe spread of misinformation, propaganda, and flawed argumentation has been amplified in the Internet era. Given the volume of data and the subtlety of identifying violations of argumentation norms, supporting information analytics ...
- research-articleApril 2023
A case-based reasoning driven ensemble learning paradigm for financial distress prediction with missing data
AbstractFinancial distress prediction is often accompanied by missing sample data. For this purpose, a novel case-based reasoning (CBR) driven ensemble learning paradigm is proposed for financial distress prediction with missing data. In the ...
Graphical abstractDisplay Omitted
Highlights- A case-based reasoning (CBR) driven ensemble learning paradigm is proposed.
- CBR-...