Paulo J. G. Lisboa

According to our database1, Paulo J. G. Lisboa authored at least 140 papers between 1992 and 2020.

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

Timeline

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Bibliography

2020
A Novel Approach to Detecting Epistasis using Random Sampling Regularisation.
IEEE ACM Trans. Comput. Biol. Bioinform., 2020

Utilizing Deep Learning and Genome Wide Association Studies for Epistatic-Driven Preterm Birth Classification in African-American Women.
IEEE ACM Trans. Comput. Biol. Bioinform., 2020

Probabilistic quantum clustering.
Knowl. Based Syst., 2020

Efficient Estimation of General Additive Neural Networks: A Case Study for CTG Data.
Proceedings of the ECML PKDD 2020 Workshops, 2020

Explaining the Neural Network: A Case Study to Model the Incidence of Cervical Cancer.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2020

2019
The Partial Response Network.
CoRR, 2019

Modelling Segmented Cardiotocography Time-Series Signals Using One-Dimensional Convolutional Neural Networks for the Early Detection of Abnormal Birth Outcomes.
CoRR, 2019

A Probabilistic framework for Quantum Clustering.
CoRR, 2019

Classifying and Grouping Mammography Images into Communities Using Fisher Information Networks to Assist the Diagnosis of Breast Cancer.
Proceedings of the Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization, 2019

A Voting Ensemble Method to Assist the Diagnosis of Prostate Cancer Using Multiparametric MRI.
Proceedings of the Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization, 2019

Scalable implementation of measuring distances in a Riemannian manifold based on the Fisher Information metric.
Proceedings of the International Joint Conference on Neural Networks, 2019

Comparative Analysis for Computer-Based Decision Support: Case Study of Knee Osteoarthritis.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2019, 2019

Societal Issues in Machine Learning: When Learning from Data is Not Enough.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

Convolutional neural network for cognitive task prediction from EEG's auditory steady state responses.
Proceedings of the 5th Congress on Robotics and Neuroscience, 2019

2018
Utilising Deep Learning and Genome Wide Association Studies for Epistatic-Driven Preterm Birth Classification in African-American Women.
CoRR, 2018

A Lifelogging Platform Towards Detecting Negative Emotions in Everyday Life using Wearable Devices.
Proceedings of the 2018 IEEE International Conference on Pervasive Computing and Communications Workshops, 2018

Bioinformatics and medicine in the era of deep learning.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Robust Interpretation of Genomic Data in Chronic Obstructive Pulmonary Disease (COPD).
Proceedings of the 11th International Conference on Developments in eSystems Engineering, 2018

A Data Science Methodology Based on Machine Learning Algorithms for Flood Severity Prediction.
Proceedings of the 2018 IEEE Congress on Evolutionary Computation, 2018

Improving Type 2 Diabetes Phenotypic Classification by Combining Genetics and Conventional Risk Factors.
Proceedings of the 2018 IEEE Congress on Evolutionary Computation, 2018

2017
Quantum clustering in non-spherical data distributions: Finding a suitable number of clusters.
Neurocomputing, 2017

A robust method for the interpretation of genomic data.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

2016
Physics and Machine Learning: Emerging Paradigms.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

Performance assessment of quantum clustering in non-spherical data distributions.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

2015
Probabilistic Modeling in Machine Learning.
Proceedings of the Springer Handbook of Computational Intelligence, 2015

Hybrid Neural Network Predictive-Wavelet Image Compression System.
Neurocomputing, 2015

Wavelet-based gene selection method for survival prediction in diffuse large B-cell lymphomas patients.
Int. J. Data Min. Bioinform., 2015

Making nonlinear manifold learning models interpretable: The manifold grand tour.
Expert Syst. Appl., 2015

From raw data to data-analysis for magnetic resonance spectroscopy - the missing link: jMRUI2XML.
BMC Bioinform., 2015

Measuring scoring efficiency through goal expectancy estimation.
Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

2014
Website design: Technical, social and medical issues for self-reporting by elderly patients.
Health Informatics J., 2014

White box radial basis function classifiers with component selection for clinical prediction models.
Artif. Intell. Medicine, 2014

Automatic relevance source determination in human brain tumors using Bayesian NMF.
Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining, 2014

Semi-supervised source extraction methodology for the nosological imaging of glioblastoma response to therapy.
Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining, 2014

A framework for initialising a dynamic clustering algorithm: ART2-A.
Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining, 2014

Use of q-values to Improve a Genetic Algorithm to Identify Robust Gene Signatures.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2014

2013
Discriminant Convex Non-negative Matrix Factorization for the classification of human brain tumours.
Pattern Recognit. Lett., 2013

A principled approach to network-based classification and data representation.
Neurocomputing, 2013

Efficient identification of independence networks using mutual information.
Comput. Stat., 2013

Introduction.
BMC Bioinform., 2013

Finding reproducible cluster partitions for the k-means algorithm.
BMC Bioinform., 2013

Interpretability in Machine Learning - Principles and Practice.
Proceedings of the Fuzzy Logic and Applications - 10th International Workshop, 2013

Research directions in interpretable machine learning models.
Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

Automated selection of interaction effects in sparse kernel methods to predict pregnancy viability.
Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2013

2012
Cohort-based kernel visualisation with scatter matrices.
Pattern Recognit., 2012

Testing geographical information systems: a case study in a fire prevention support system.
J. Syst. Inf. Technol., 2012

Non-negative matrix factorisation methods for the spectral decomposition of MRS data from human brain tumours.
BMC Bioinform., 2012

Bayesian Neural Network Applied in Medical Survival Analysis of Primary Biliary Cirrhosis.
Proceedings of the 14th International Conference on Computer Modelling and Simulation, 2012

Towards interpretable classifiers with blind signal separation.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Bayesian Neural Network with and without compensation for competing risks.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Making machine learning models interpretable.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

Constructing similarity networks using the Fisher information metric.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

Multicentre study design in survival analysis.
Proceedings of the 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2012

2011
Clustering of protein expression data: a benchmark of statistical and neural approaches.
Soft Comput., 2011

Issues in online patient self-reporting of health status.
Health Informatics J., 2011

Model Selection with PLANN-CR-ARD.
Proceedings of the Advances in Computational Intelligence, 2011

Spectral decomposition methods for the analysis of MRS information from human brain tumors.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

PLANN-CR-ARD model predictions and Non-parametric estimates with Confidence Intervals.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Brain Tumor Pathological Area Delimitation through Non-negative Matrix Factorization.
Proceedings of the Data Mining Workshops (ICDMW), 2011

Seeing is believing: The importance of visualization in real-world machine learning applications.
Proceedings of the ESANN 2011, 2011

The role of Fisher information in primary data space for neighbourhood mapping.
Proceedings of the ESANN 2011, 2011

Scenario Analysis for Local Area Life Expectancy Using Conditional Independence Maps.
Proceedings of the 2011 Developments in E-systems Engineering, 2011

Clustering categorical data: A stability analysis framework.
Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2011

Discovering Hidden Pathways in Bioinformatics.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2011

2010
Data Mining in Cancer Research [Application Notes].
IEEE Comput. Intell. Mag., 2010

A methodology to identify consensus classes from clustering algorithms applied to immunohistochemical data from breast cancer patients.
Comput. Biol. Medicine, 2010

Cohort-based kernel visualisation with scatter matrices.
Proceedings of the International Joint Conference on Neural Networks, 2010

Assessment of benefit vs. risk of drug therapy: The potential for outcome analysis with flexible models.
Proceedings of the International Joint Conference on Neural Networks, 2010

Flexible parametric modelling of the hazard function in breast cancer studies.
Proceedings of the International Joint Conference on Neural Networks, 2010

A Clinical Decision Support System for Breast Cancer Patients.
Proceedings of the Emerging Trends in Technological Innovation, 2010

Computational Intelligence in biomedicine: Some contributions.
Proceedings of the ESANN 2010, 2010

2009
Short-term time-to-event model of response to treatment following the GIMEMA protocol for Acute Myeloid Leukaemia.
Proceedings of the Computational Intelligence and Bioengineering, 2009

An AI Walk from Pharmacokinetics to A Marketing.
Proceedings of the Encyclopedia of Artificial Intelligence (3 Volumes), 2009

Partial Logistic Artificial Neural Network for Competing Risks Regularized With Automatic Relevance Determination.
IEEE Trans. Neural Networks, 2009

Novel hybrid classified vector quantization using discrete cosine transform for image compression.
J. Electronic Imaging, 2009

Survival analysis in cancer using a partial logistic neural network model with Bayesian regularisation framework: a validation study.
Int. J. Knowl. Eng. Soft Data Paradigms, 2009

Editorial.
Int. J. Knowl. Eng. Soft Data Paradigms, 2009

Evaluation of missing data imputation in longitudinal cohort studies in breast cancer survival.
Int. J. Knowl. Eng. Soft Data Paradigms, 2009

Determination of mode of ventilation using OSRE.
Comput. Biol. Medicine, 2009

How to find simple and accurate rules for viral protease cleavage specificities.
BMC Bioinform., 2009

Grocery shopping recommendations based on basket-sensitive random walk.
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

Stratification Methodologies for Neural Networks Models of Survival.
Proceedings of the Bio-Inspired Systems: Computational and Ambient Intelligence, 2009

Patient stratification with competing risks by multivariate Fisher distance.
Proceedings of the International Joint Conference on Neural Networks, 2009

Adaptive Classified Vector Quantisation of Non-orthogonal Representations of Images and its Application to Image Compression.
Proceedings of the First International Conference on Computational Intelligence, 2009

Different Methodologies for Patient Stratification Using Survival Data.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2009

2008
Cluster-based visualisation with scatter matrices.
Pattern Recognit. Lett., 2008

Time-to-event analysis with artificial neural networks: An integrated analytical and rule-based study for breast cancer.
Neural Networks, 2008

Financial time series prediction using polynomial pipelined neural networks.
Expert Syst. Appl., 2008

An integrated framework for risk profiling of breast cancer patients following surgery.
Artif. Intell. Medicine, 2008

The value of personalised recommender systems to e-business: a case study.
Proceedings of the 2008 ACM Conference on Recommender Systems, 2008

Stratification of Severity of Illness Indices: A Case Study for Breast Cancer Prognosis.
Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2008

Are Model-Based Clustering and Neural Clustering Consistent? A Case Study from Bioinformatics.
Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2008

An adaptive hybrid image compression method and its application to medical images.
Proceedings of the 2008 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2008

External Validation of a Bayesian Neural Network Model in Survival Analysis.
Proceedings of the Seventh International Conference on Machine Learning and Applications, 2008

Classification, Dimensionality Reduction, and Maximally Discriminatory Visualization of a Multicentre 1H-MRS Database of Brain Tumors.
Proceedings of the Seventh International Conference on Machine Learning and Applications, 2008

Missing Data Imputation in Longitudinal Cohort Studies: Application of PLANN-ARD in Breast Cancer Survival.
Proceedings of the Seventh International Conference on Machine Learning and Applications, 2008

Machine learning in cancer research: implications for personalised medicine.
Proceedings of the ESANN 2008, 2008

An Adaptive Hybrid Classified Vector Quantisation and its Application to Image Compression.
Proceedings of the EMS 2008, 2008

2007
Removal of eye movement artefacts from single channel recordings of retinal evoked potentials using <i>synchronous</i> dynamical embedding and independent component analysis.
Medical Biol. Eng. Comput., 2007

An approach based on the Adaptive Resonance Theory for analysing the viability of recommender systems in a citizen Web portal.
Expert Syst. Appl., 2007

Double-blind evaluation and benchmarking of survival models in a multi-centre study.
Comput. Biol. Medicine, 2007

A probabilistic model for item-based recommender systems.
Proceedings of the 2007 ACM Conference on Recommender Systems, 2007

Neural Networks and Other Machine Learning Methods in Cancer Research.
Proceedings of the Computational and Ambient Intelligence, 2007

A Prototype Integrated Decision Support System for Breast Cancer Oncology.
Proceedings of the Computational and Ambient Intelligence, 2007

Comparing Analytical Decision Support Models Through Boolean Rule Extraction: A Case Study of Ovarian Tumour Malignancy.
Proceedings of the Advances in Neural Networks, 2007

Assessing flexible models and rule extraction from censored survival data.
Proceedings of the International Joint Conference on Neural Networks, 2007

Evaluating Retail Recommender Systems via Retrospective Data: Lessons Learnt from a Live-Intervention Study.
Proceedings of the 2007 International Conference on Data Mining, 2007

2006
Orthogonal search-based rule extraction (OSRE) for trained neural networks: a practical and efficient approach.
IEEE Trans. Neural Networks, 2006

The use of artificial neural networks in decision support in cancer: A systematic review.
Neural Networks, 2006

Robust analysis of MRS brain tumour data using <i>t</i>-GTM.
Neurocomputing, 2006

Handling outliers in brain tumour MRS data analysis through robust topographic mapping.
Comput. Biol. Medicine, 2006

iShakti - Crossing the Digital Divide in Rural India.
Proceedings of the 2006 IEEE / WIC / ACM International Conference on Web Intelligence (WI 2006), 2006

Learning what is important: feature selection and rule extraction in a virtual course.
Proceedings of the ESANN 2006, 2006

Polynomial Pipelined Neural Network and Its Application to Financial Time Series Prediction.
Proceedings of the AI 2006: Advances in Artificial Intelligence, 2006

2005
Level estimation, classification and probability distribution architectures for trading the EUR/USD exchange rate.
Neural Comput. Appl., 2005

Handling outliers and missing data in brain tumour clinical assessment using t-GTM.
Proceedings of the ESANN 2005, 2005

Functional topographic mapping for robust handling of outliers in brain tumour data.
Proceedings of the ESANN 2005, 2005

2004
Cluster-Based Visualisation of Marketing Data.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2004

2003
Selective smoothing of the generative topographic mapping.
IEEE Trans. Neural Networks, 2003

A Bayesian neural network approach for modelling censored data with an application to prognosis after surgery for breast cancer.
Artif. Intell. Medicine, 2003

2002
A review of evidence of health benefit from artificial neural networks in medical intervention.
Neural Networks, 2002

Minimal MLPs do not model the XOR logic.
Neurocomputing, 2002

Comparison of Nested Simulated Annealing and Reactive Tabu Search for Efficient Experimental Designs with Correlated Data.
Proceedings of the COMPSTAT 2002, 2002

2001
An Electronic Commerce Application of the Bayesian Framework for MLPs: The Effect of Marginalisation and ARD.
Neural Comput. Appl., 2001

2000
Bias reduction in skewed binary classification with Bayesian neural networks.
Neural Networks, 2000

Quantitative Characterization and Prediction of On-Line Purchasing Behavior: A Latent Variable Approach.
Int. J. Electron. Commer., 2000

The generative topographic mapping as a principal model for data visualization and market segmentation: an electronic commerce case.
Int. J. Comput. Syst. Signals, 2000

Segmenting the e-Commerce Market Using the Generative Topographic Mapping.
Proceedings of the MICAI 2000: Advances in Artificial Intelligence, 2000

The Role of Multiple, Linear-Projection Based Visualization Techniques in RBF-Based Classification of High Dimensional Data.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

Outstanding Issues for Clinical Decision Support with Neural Networks.
Proceedings of the Artificial Neural Networks in Medicine and Biology, 2000

Introduction.
Proceedings of the Artificial Neural Networks in Biomedicine, 2000

1999
An Implementation of the Hough Transformation for the Identification and Labelling of Fixed Period Sinusoidal Curves.
Comput. Vis. Image Underst., 1999

Dealing with censorship in neural network models.
Proceedings of the International Joint Conference Neural Networks, 1999

1997
Tissue characterisation with NMR spectroscopy: current state and future prospects for the application of neural networks analysis.
Proceedings of International Conference on Neural Networks (ICNN'97), 1997

Fast face recognition method using a multistage hierarchical network.
Proceedings of the 1997 IEEE International Conference on Acoustics, 1997

1996
Enhancing the non-linear modelling capabilities of MLP neural networks using spread encoding.
Fuzzy Sets Syst., 1996

Neural network modelling and control for underwater vehicles.
Artif. Intell. Eng., 1996

1993
Techniques and applications of neural networks.
Ellis Horwood workshop series, Ellis Horwood, ISBN: 978-0-13-062183-2, 1993

1992
Translation, rotation, and scale invariant pattern recognition by high-order neural networks and moment classifiers.
IEEE Trans. Neural Networks, 1992

The role of local scale and orientation in feature location using neural nets.
Proceedings of the 11th IAPR International Conference on Pattern Recognition, 1992


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