Sara Madeira

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Faculdade de Ciências da Universidade de Lisboa

Portugal

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Recent Grants

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AIpALS - Advanced learnIng models using Patient profiles and disease progression patterns for prognostic prediction

Open Date: 2021-03-01

Close Date:

Grant: Close

BRAINTEASER - BRinging Artificial INTelligencE home for a better cAre of amyotrophic lateral sclerosis and multiple SclERosis

Open Date: 2021-01-01

Close Date:

Grant: Close

LAIfeBlood - Artificial Intelligence for Blood Management

Open Date: 2020-01-01

Close Date: 2022-12-01

Grant: Close

PREDICT - Personalized therapy for RhEumatic DIseases via machine learning

Open Date: 2019-01-01

Close Date: 2021-12-01

Grant: Close

CIRCLES - Controlling mIcRobiomes CircuLations for bEtterfood Systems

Open Date: 2018-11-01

Close Date:

Articles (18)

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2026

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2024

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2022

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2022

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2022

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2022

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2022

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2022

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2022

Collaborators (9)

Diogo Soares

Invited Teaching Assistant

Faculdade de Ciências da Universidade de Lisboa

PORTUGAL

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Hugo Gamboa

Associate Professor (with Habilitation)

Faculdade de Ciências da Universidade de Lisboa

PORTUGAL

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Eduardo Castanho

Guest Assistant Professor

Instituto Politécnico de Leiria Escola Superior de Tecnologia e Gestão

PORTUGAL

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Erica Tavazzi

University of Padova

ITALY

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Rui Henriques

Assistant Professor

Universidade de Lisboa Instituto Superior Técnico

PORTUGAL

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Marília Barandas

Fraunhofer Portugal Research

PORTUGAL

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Bruno Miranda

University of Lisbon

PORTUGAL

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Helena Aidos

Assistant Professor

Faculdade de Ciências da Universidade de Lisboa

PORTUGAL

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Enrico Longato

University of Padua

ITALY

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Sara Madeira

Research Interests

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Recent Grants

Articles (18)

Cutting through the noise: Explaining residuals in multivariate time series with motif analysis

TriHSPAM: Triclustering heterogeneous longitudinal clinical data using sequential patterns

Temporal stratification of amyotrophic lateral sclerosis patients using disease progression patterns

A Comprehensive Survey on Biclustering-based Collaborative Filtering

Comprehensive assessment of triclustering algorithms for three-way temporal data analysis

Biclustering data analysis: a comprehensive survey

Artificial intelligence and statistical methods for stratification and prediction of progression in amyotrophic lateral sclerosis: A systematic review

Triclustering-based classification of longitudinal data for prognostic prediction: targeting relevant clinical endpoints in amyotrophic lateral sclerosis

Short-term electricity load forecastingA systematic approach from system level to secondary substations

G-bic: generating synthetic benchmarks for biclustering

Actionable descriptors of spatiotemporal urban dynamics from large-scale mobile data: A case study in Lisbon city

Learning prognostic models using a mixture of biclustering and triclustering: Predicting the need for non-invasive ventilation in Amyotrophic Lateral Sclerosis

Impact of metrics on biclustering solution and quality: A review

Posture Risk Assessment in an Automotive Assembly Line using Inertial Sensors

Water Consumption Pattern Analysis Using Biclustering: When, Why and How

Biclustering fMRI time series: a comparative study

Dynamic Bayesian networks for stratification of disease progression in amyotrophic lateral sclerosis

Shapelets to Classify Energy Demand Time Series

Collaborators (9)

Diogo Soares

Hugo Gamboa

Eduardo Castanho

Erica Tavazzi

Rui Henriques

Marília Barandas

Bruno Miranda

Helena Aidos

Enrico Longato

Make your next move.

Sara Madeira

Research Interests

Explore related searches

Contact this professor

Recent Grants

Articles (18)

Cutting through the noise: Explaining residuals in multivariate time series with motif analysis

TriHSPAM: Triclustering heterogeneous longitudinal clinical data using sequential patterns

Temporal stratification of amyotrophic lateral sclerosis patients using disease progression patterns

A Comprehensive Survey on Biclustering-based Collaborative Filtering

Comprehensive assessment of triclustering algorithms for three-way temporal data analysis

Biclustering data analysis: a comprehensive survey

Artificial intelligence and statistical methods for stratification and prediction of progression in amyotrophic lateral sclerosis: A systematic review

Triclustering-based classification of longitudinal data for prognostic prediction: targeting relevant clinical endpoints in amyotrophic lateral sclerosis

Short-term electricity load forecastingA systematic approach from system level to secondary substations

G-bic: generating synthetic benchmarks for biclustering

Actionable descriptors of spatiotemporal urban dynamics from large-scale mobile data: A case study in Lisbon city

Learning prognostic models using a mixture of biclustering and triclustering: Predicting the need for non-invasive ventilation in Amyotrophic Lateral Sclerosis

Impact of metrics on biclustering solution and quality: A review

Posture Risk Assessment in an Automotive Assembly Line using Inertial Sensors

Water Consumption Pattern Analysis Using Biclustering: When, Why and How

Biclustering fMRI time series: a comparative study

Dynamic Bayesian networks for stratification of disease progression in amyotrophic lateral sclerosis

Shapelets to Classify Energy Demand Time Series

Collaborators (9)

Diogo Soares

Hugo Gamboa

Eduardo Castanho

Erica Tavazzi

Rui Henriques

Marília Barandas

Bruno Miranda

Helena Aidos

Enrico Longato

Make your next move.

Short-term electricity load forecastingA systematic approach from system level to secondary substations