Cecília Maria Vasconcelos Costa e Castro

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University of Minho

Portugal

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About

Professor Cecília Maria Vasconcelos Costa e Castro is a faculty member at Universidade do Minho in Portugal. Her research areas encompass mathematical modeling, data analytics, and health sciences, with recent publications addressing topics such as kidney diseases, COVID-19 dynamics, and artificial intelligence in clinical trials. She is also engaged in the study of fatigue-life distributions and science communication in the geoscience community.

Recent Grants

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Projecto Estratégico - UI 13 - 2011-2012

Open Date: 2011-01-01

Close Date: 2013-12-31

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Collaborators (4)

Diamantino Pereira

University of Minho

PORTUGAL

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Ana Cristina Braga

Assistant Professor

University of Minho

PORTUGAL

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Ana Paula Amorim

University of Minho

PORTUGAL

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Elsa Costa e Silva

Professor Doctor at University of Minho

University of Minho

PORTUGAL

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Cecília Maria Vasconcelos Costa e Castro

Research Interests

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About

Recent Grants

Articles (30)

Molecular hydrogen and kidney diseases: a scoping review based on scientometry and data analytics

Profiling the geoscience community: exploring patterns of science communication and public engagement

Revisiting fatigue-life distributions of Birnbaum-Saunders type: Mathematical characterization, simulation study, and applications

Asthma and severe acute respiratory infections: a stratified analysis of mortality patterns in Brazil

Bivariate extended skew-elliptical Heckman models: mathematical characterization and an application in economic sciences

Multi-strain COVID-19 dynamics with vaccination strategies: Mathematical modeling and case study

Total time on test-based goodness-of-fit statistics for the reciprocal property in fatigue-life models

Artificial intelligence and blockchain in clinical trials: enhancing data governance efficiency, integrity, and transparency

A Real-Time Intelligent System Based on Machine-Learning Methods for Improving Communication in Sign Language

Confidence Intervals for the Reliability of Dependent Systems: Integrating Frailty Models and Copula-Based Methods

Blockchain in clinical trials: Bibliometric and network studies of applications, challenges, and future prospects based on data analytics

A Statistical Methodology for Evaluating Asymmetry after Normalization with Application to Genomic Data

Skew-Normal Inflated Models: Mathematical Characterization and Applications to Medical Data with Excess of Zeros and Ones

Security Control for a Fuzzy System under Dynamic Protocols and Cyber-Attacks with Engineering Applications

Combining Advanced Feature-Selection Methods to Uncover Atypical Energy-Consumption Patterns

Modeling Residential Energy Consumption Patterns with Machine Learning Methods Based on a Case Study in Brazil

Solvability and algorithm for Sylvester-type quaternion matrix equations with potential applications

Optimizing Sentiment Analysis Models for Customer Support: Methodology and Case Study in the Portuguese Retail Sector

Unveiling patterns and trends in research on cumulative damage models for statistical and reliability analyses: Bibliometric and thematic explorations with data analytics

Optimized design and analysis of cable-based parallel manipulators for enhanced subsea operations

Advanced Mathematical Approaches in Psycholinguistic Data Analysis: A Methodological Insight

Quasi-Cauchy Regression Modeling for Fractiles Based on Data Supported in the Unit Interval

An Overview of Kriging and Cokriging Predictors for Functional Random Fields

Fractional Transformation-Based Decentralized Robust Control of a Coupled-Tank System for Industrial Applications

An Overview of Forecast Analysis with ARIMA Models during the COVID-19 Pandemic: Methodology and Case Study in Brazil

An Overview of Forecast Analysis with ARIMA Models during the COVID-19 Pandemic: Methodology and Case Study in Brazil

Biased Random-Key Genetic Algorithm with Local Search Applied to the Maximum Diversity Problem

Biased Random-Key Genetic Algorithm with Local Search Applied to the Maximum Diversity Problem

On Fuzzy and Crisp Solutions of a Novel Fractional Pandemic Model

On Fuzzy and Crisp Solutions of a Novel Fractional Pandemic Model

Collaborators (4)

Diamantino Pereira

Ana Cristina Braga

Ana Paula Amorim

Elsa Costa e Silva

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