Rui Camacho

Domains

Artificial Intelligence and Decision Support Artificial Intelligence

Projects

RECAP

The overall aim of the project is to improve the health, development and quality of life of children and adults born preterm (< 32 weeks) or with low weight (< 1500g). They constitute fewer than 2% of all births across Europe, but account for up to half of perinatal and infant deaths, and more than a third of the health and educational budgets for children. It will be achieved by developing a sustainable, geographically diverse and multidisciplinary platform of national and European cohorts of VPT/VLBW, over a 30-year time span. Novel methodologies and tools for data management and analysis will be developed to strengthen research on current and future VPT/VLBW cohorts.

Research on European Children and Adults born Preterm

EUCAN_CONNECT

A federated FAIR platform enabling large-scale analysis of high-value cohort data connecting Europe and Canada in personalized health

Publications

Imitation learning for aerobatic maneuvering in fixed-wing aircraft

Freitas, H;Camacho, R;Silva, DC;

2024

JOURNAL OF COMPUTATIONAL SCIENCE

A Deep Learning approach to infer morphological characteristics of the heart from cardiac sound analysis

Andrade, L;Camacho, R;Oliveira, J;

2023

2023 13TH INTERNATIONAL CONFERENCE ON BIOSCIENCE, BIOCHEMISTRY AND BIOINFORMATICS, ICBBB 2023

Federated Learning in Medical Image Analysis: A Systematic Survey

da Silva, FR;Camacho, R;Tavares, JMRS;

2024

ELECTRONICS

Unsupervised Online Event Ranking for IT Operations

Mendes, TC;Barata, AA;Pereira, M;Moreira, JM;Camacho, R;Sousa, RT;

2023

Intelligent Data Engineering and Automated Learning - IDEAL 2023 - 24th International Conference, Évora, Portugal, November 22-24, 2023, Proceedings

View all publications

Supervised theses

Crowd-computing hybrids in scientific discovery

António José Guilherme Correia

D - 2023

UTAD-ECT

Centres

Artificial Intelligence and Decision Support

Our Laboratory of Artificial Intelligence and Decision Support (LIAAD) conducts research in the fields of Artificial Intelligence, Machine Learning, Data Science, and Modelling. These areas are cross-cutting and apply to all sectors of society and the economy. The vast amounts of data being collected, alongside the ubiquity of digitalisation and sensorisation, are increasingly creating opportunities and challenges for automating decision support. The combination of Machine Learning and complex models is transforming the economy, healthcare, justice, industry, science, public administration, and education. This encourages us to invest in diverse technological and scientific approaches and perspectives. Our overarching strategy is to explore the flow and diversification of data, and to invest in research lines that will lead to the development of applied Artificial Intelligence foundations and models that are responsible and human centred.