Yamisleydi Salgueiro
Biographic Data
| ID | 8970865 |
|---|---|
| NAME | Yamisleydi Salgueiro |
| GIVEN NAMES | Yamisleydi |
| FAMILY NAME | Salgueiro |
| SIGNATURE | SALGUEIRO Y |
| AFFILIATIONS | University of Talca |
| ORCID | 0000-0002-1946-0053 |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Modeling depression trends through continuous cognitive mapping
Modeling the global burden of depression presents significant challenges due to the chronic, dynamic, and heterogeneous nature of the disease. While Fuzzy Cognitive Maps (FCMs) provide an interpretable framework for modeling relational dynamics, conventional formulations often suffer from numerical saturation and a limited ability to capture structurally diverse solution spaces. In this paper, we propose a Continuous Fuzzy Cognitive Map (cFCM) fr…
Mitigating implicit and explicit bias in structured data without sacrificing accuracy in pattern classification
Using biased data to train Artificial Intelligence (AI) algorithms will lead to biased decisions, discriminating against certain groups or individuals. Bias can be explicit (one or several protected features directly influence the decisions) or implicit (one or several protected features indirectly influence the decisions). Unsurprisingly, biased patterns are difficult to detect and mitigate. This paper investigates the extent to which explicit a…
No prominent works on this page.
Mitigating implicit and explicit bias in structured data without sacrificing accuracy in pattern classification
Using biased data to train Artificial Intelligence (AI) algorithms will lead to biased decisions, discriminating against certain groups or individuals. Bias can be explicit (one or several protected features directly influence the decisions) or implicit (one or several protected features indirectly influence the decisions). Unsurprisingly, biased patterns are difficult to detect and mitigate. This paper investigates the extent to which explicit a…
Modeling depression trends through continuous cognitive mapping
Modeling the global burden of depression presents significant challenges due to the chronic, dynamic, and heterogeneous nature of the disease. While Fuzzy Cognitive Maps (FCMs) provide an interpretable framework for modeling relational dynamics, conventional formulations often suffer from numerical saturation and a limited ability to capture structurally diverse solution spaces. In this paper, we propose a Continuous Fuzzy Cognitive Map (cFCM) fr…
Artificial Intelligence (1 work) · Categorization (1 work) · Centrality (1 work) · Cluster analysis (1 work) · Cognition (1 work) · Cognitive map (1 work) · Cognitive psychology (1 work) · Cognitive Science and Mapping (1 work) · Computer Science (1 work) · Data mining (1 work)