Alexandra M. Carvalho

Orcid: 0000-0001-6607-7711

According to our database1, Alexandra M. Carvalho authored at least 40 papers between 2004 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Using Markov chains and temporal alignment to identify clinical patterns in Dementia.
J. Biomed. Informatics, April, 2023

Zgli: A Pipeline for Clustering by Compression with Application to Patient Stratification in Spondyloarthritis.
Sensors, February, 2023

Comparative Analysis of Machine Learning Models for Time-Series Forecasting of Escherichia Coli Contamination in Portuguese Shellfish Production Areas.
Proceedings of the Machine Learning, Optimization, and Data Science, 2023

Causal Graph Discovery for Explainable Insights on Marine Biotoxin Shellfish Contamination.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2023, 2023

Evaluating the Causal Role of Environmental Data in Shellfish Biotoxin Contamination on the Portuguese Coast.
Proceedings of the Progress in Artificial Intelligence, 2023

2022
Model Complexity in Statistical Manifolds: The Role of Curvature.
IEEE Trans. Inf. Theory, 2022

2021
Learning dynamic Bayesian networks from time-dependent and time-independent data: Unraveling disease progression in Amyotrophic Lateral Sclerosis.
J. Biomed. Informatics, 2021

Coupling sparse Cox models with clustering of longitudinal transcriptomics data for trauma prognosis.
BioData Min., 2021

2020
Information-Theoretical Criteria for Characterizing the Earliness of Time-Series Data.
Entropy, 2020

On the minmax regret for statistical manifolds: the role of curvature.
CoRR, 2020

Sparse Consensus Classification for Discovering Novel Biomarkers in Rheumatoid Arthritis.
Proceedings of the Machine Learning, Optimization, and Data Science, 2020

Predictive Medicine Using Interpretable Recurrent Neural Networks.
Proceedings of the Pattern Recognition. ICPR International Workshops and Challenges, 2020

Latent Variable Modelling and Variational Inference for scRNA-seq Differential Expression Analysis.
Proceedings of the Computational Advances in Bio and Medical Sciences, 2020

2019
AliClu - Temporal sequence alignment for clustering longitudinal clinical data.
BMC Medical Informatics Decis. Mak., 2019

Modelling cancer outcomes of bone metastatic patients: combining survival data with N-Telopeptide of type I collagen (NTX) dynamics through joint models.
BMC Medical Informatics Decis. Mak., 2019

MSAX: Multivariate Symbolic Aggregate Approximation for Time Series Classification.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2019

2018
Polynomial-Time Algorithm for Learning Optimal BFS-Consistent Dynamic Bayesian Networks.
Entropy, 2018

Model selection for clustering of pharmacokinetic responses.
Comput. Methods Programs Biomed., 2018

Learning Consistent Tree-Augmented Dynamic Bayesian Networks.
Proceedings of the Machine Learning, Optimization, and Data Science, 2018

Unravelling Breast and Prostate Common Gene Signatures by Bayesian Network Learning.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2018

Variational Inference in Probabilistic Single-cell RNA-seq Models.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2018

2017
Unsupervised learning of pharmacokinetic responses.
Comput. Stat., 2017

2015
Polynomial-time algorithm for learning optimal tree-augmented dynamic Bayesian networks.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Outlier Detection in Cox Proportional Hazards Models Based on the Concordance c-Index.
Proceedings of the Machine Learning, Optimization, and Big Data, 2015

Outlier Detection in Survival Analysis based on the Concordance C-index.
Proceedings of the BIOINFORMATICS 2015, 2015

2014
Hybrid learning of Bayesian multinets for binary classification.
Pattern Recognit., 2014

2013
Efficient Approximation of the Conditional Relative Entropy with Applications to Discriminative Learning of Bayesian Network Classifiers.
Entropy, 2013

Class Imbalance in the Prediction of Dementia from Neuropsychological Data.
Proceedings of the Progress in Artificial Intelligence, 2013

2012
Pattern matching through Chaos Game Representation: bridging numerical and discrete data structures for biological sequence analysis.
Algorithms Mol. Biol., 2012

2011
Motif representation and discovery.
PhD thesis, 2011

Discriminative Learning of Bayesian Networks via Factorized Conditional Log-Likelihood.
J. Mach. Learn. Res., 2011

GRISOTTO: A greedy approach to improve combinatorial algorithms for motif discovery with prior knowledge.
Algorithms Mol. Biol., 2011

2008
YEASTRACT-DISCOVERER: new tools to improve the analysis of transcriptional regulatory associations in <i>Saccharomyces cerevisiae</i>.
Nucleic Acids Res., 2008

2007
Learning bayesian networks consistent with the optimal branching.
Proceedings of the Sixth International Conference on Machine Learning and Applications, 2007

Efficient Learning of Bayesian Network Classifiers.
Proceedings of the AI 2007: Advances in Artificial Intelligence, 2007

2006
An Efficient Algorithm for the Identification of Structured Motifs in DNA Promoter Sequences.
IEEE ACM Trans. Comput. Biol. Bioinform., 2006

RISOTTO: Fast Extraction of Motifs with Mismatches.
Proceedings of the LATIN 2006: Theoretical Informatics, 2006

2005
A highly scalable algorithm for the extraction of CIS-regulatory regions.
Proceedings of 3rd Asia-Pacific Bioinformatics Conference, 17-21 January 2005, Singapore, 2005

2004
Efficient Extraction of Structured Motifs Using Box-Links.
Proceedings of the String Processing and Information Retrieval, 2004

A parallel algorithm for the extraction of structured motifs.
Proceedings of the 2004 ACM Symposium on Applied Computing (SAC), 2004


  Loading...