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About

I am a lecturer in the Department of Computer Science, School of Sciences of University of Porto, Portugal. I obtained a B.Sc. degree in Computer Science from State University of Rio de Janeiro, Brazil, in 1985, and an M.Sc. degree in the Systems Engineering and Computer Science department of Federal University of Rio de Janeiro, Brazil, in 1988. My Ph.D. degree was obtained from Bristol University, UK, in 1995. In 1998, I started as a lecturer in the Department of Systems Engineering and Computer Science of COPPE, an institution for postgraduate studies in Engineering, at Federal University of Rio de Janeiro, where I taught courses on Operating Systems, Concurrent Programming and Topics on High Performance Computing, at M.Sc. and Ph.D. levels, and Artificial Intelligence and Logic Programming, at undergraduate level. In Februrary 2007 I moved to Portugal where I am now located. During the periods between October 2001 and December 2002, April 2004 and March 2005, Aug 2010 and Feb 2011, and Oct 2014 and Mar 2015, I worked as a visiting researcher at University of Wisconsin-Madison, USA, in the department of Biostatistics and Medical Informatics, and at the Radiology Department of the School of Sciences and Public Health. During these periods, I worked for machine learning projects funded by NSF, DARPA and American Air Force (projects COLLEAGUE, EELD and EAGLE), and NLM (Project ABLe) and started to work with applications that demanded a huge amount of resources. At this time, I had the opportunity to work with the Condor team, and to largely use the Condor resource manager to run experiments. My main research areas are Logic programming, Inductive Logic Programming, and Parallel Logic Programming systems. I served as Program Comittee member of several workshops and conferences in these areas. I supervised several M.Sc. and Ph.D. students in these areas. I have more than 80 publications in conferences and journals. I also participated or was the principal investigator of several projects funded by CNPq (Brazil), FCT (Portugal) and the EU. I am a member of the EELA (E-science grid facility for Europe and Latin America) initiative, whose main objective is to promote and maintain the infrastructure of hardware and software between Europe and Latin America. Currently, I have been working on machine learning techniques based on Inductive Logic programming, but still using parallelzation and grid environments to be able to perform machine learning experiments.

Interest
Topics
Details

Details

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Publications

2021

Simple Matrix Factorization Collaborative Filtering for Drug Repositioning on Cell Lines

Authors
Carrera, I; Tejera, E; Dutra, I;

Publication
Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2021, Volume 5: HEALTHINF, Online Streaming, February 11-13, 2021.

Abstract

2020

Representing Cellular Lines with SVM and Text Processing

Authors
Carrera, I; Dutra, I; Tejera, E;

Publication
BCB '20: 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, Virtual Event, USA, September 21-24, 2020

Abstract

2020

Clinical decision support systems for pressure ulcer management: a systematic review (Preprint)

Authors
Araujo, SM; Sousa, P; Dutra, I;

Publication
JMIR Medical Informatics

Abstract

2020

Clinical Decision Support Systems for Pressure Ulcer Management: Systematic Review (Preprint)

Authors
Araujo, SM; Sousa, P; Dutra, I;

Publication

Abstract
BACKGROUND

The clinical decision-making process in pressure ulcer management is complex, and its quality depends on both the nurse's experience and the availability of scientific knowledge. This process should follow evidence-based practices incorporating health information technologies to assist health care professionals, such as the use of clinical decision support systems. These systems, in addition to increasing the quality of care provided, can reduce errors and costs in health care. However, the widespread use of clinical decision support systems still has limited evidence, indicating the need to identify and evaluate its effects on nursing clinical practice.

OBJECTIVE

The goal of the review was to identify the effects of nurses using clinical decision support systems on clinical decision making for pressure ulcer management.

METHODS

The systematic review was conducted in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations. The search was conducted in April 2019 on 5 electronic databases: MEDLINE, SCOPUS, Web of Science, Cochrane, and CINAHL, without publication date or study design restrictions. Articles that addressed the use of computerized clinical decision support systems in pressure ulcer care applied in clinical practice were included. The reference lists of eligible articles were searched manually. The Mixed Methods Appraisal Tool was used to assess the methodological quality of the studies.

RESULTS

The search strategy resulted in 998 articles, 16 of which were included. The year of publication ranged from 1995 to 2017, with 45% of studies conducted in the United States. Most addressed the use of clinical decision support systems by nurses in pressure ulcers prevention in inpatient units. All studies described knowledge-based systems that assessed the effects on clinical decision making, clinical effects secondary to clinical decision support system use, or factors that influenced the use or intention to use clinical decision support systems by health professionals and the success of their implementation in nursing practice.

CONCLUSIONS

The evidence in the available literature about the effects of clinical decision support systems (used by nurses) on decision making for pressure ulcer prevention and treatment is still insufficient. No significant effects were found on nurses' knowledge following the integration of clinical decision support systems into the workflow, with assessments made for a brief period of up to 6 months. Clinical effects, such as outcomes in the incidence and prevalence of pressure ulcers, remain limited in the studies, and most found clinically but nonstatistically significant results in decreasing pressure ulcers. It is necessary to carry out studies that prioritize better adoption and interaction of nurses with clinical decision support systems, as well as studies with a representative sample of health care professionals, randomized study designs, and application of assessment instruments appropriate to the professional and institutional profile. In addition, long-term follow-up is necessary to assess the effects of clinical decision support systems that can demonstrate a more real, measurable, and significant effect on clinical decision making.

CLINICALTRIAL

PROSPERO International Prospective Register of Systematic Reviews CRD42019127663; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=127663

2020

Diabetes Management Guidance by a Logical Unit Supported by Data-Mining in a Mobile Application

Authors
Machado, D; Costa, VS; Dutra, I; Brandao, P;

Publication
XV MEDITERRANEAN CONFERENCE ON MEDICAL AND BIOLOGICAL ENGINEERING AND COMPUTING - MEDICON 2019

Abstract
Diabetes type I is a chronic disease that requires strict supervision. MyDiabetes is a utility application for diabetic users. This application served as basis to develop a logical unit, composed of logical rules, translated from medical protocols and guidelines, to advise the user. The data in the application is a source of knowledge about the user's health state and diabetes intrinsic characteristics. An existing concern is the weak user adherence and consequential data absence. The implemented solutions were gamification and an interface rework. As later confirmed through a survey, users feel captivated by appealing interfaces, achievements and medals. In a near future, we will resume our work with the S. Joao's hospital, with a new trial and volunteers. User testing will be used to validate the gamification techniques.

Supervised
thesis

2019

Towards Improving the Search for Multi-Relational Concepts in ILP

Author
Alberto José Rajão Barbosa

Institution
UP-FCUP

2019

Exascale computing with custom Linear Mixed Model kernels and GPU accelerators for Genomic Wide Association Studies and personalized medicine

Author
Christopher David Harrison

Institution
UP-FCUP

2017

Execução e Gestão de Aplicações Conteinerizadas

Author
Diogo Cristiano dos Santos Reis

Institution
UP-FCUP

2017

Improving the search for multi-relational concepts in ILP

Author
Alberto José Rajão Barbosa

Institution
UP-FCUP

2017

Weighted Multiple Kernel Learning for Breast Cancer Diagnosis applied to Mammograms

Author
Tiago André Guedes Santos

Institution
UP-FCUP