Filipe Portela

University of Minho

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Trends

Author Order

Document Type

Co-Authors

Manuel Filipe Santos

University of Minho

183

José Machado

University of Minho

128

António Abelha

University of Minho

128

Fernando Rua

Centro Hospitalar do Porto

ÁS

Álvaro Silva

Universidade Federal da Paraíba

José Neves

Hospital de Santa Cruz

Eliana Pereira

University of Minho

Andreia Brandão

University of Minho

Luciana Cardoso

Instituto Federal Goiano

Fernando Marins

University of Minho

Cooperative Institutions

University of Minho

135

Universidade do Porto

University of Lisbon

Universidade Federal do Pará

Universidade de São Paulo

Centro Hospitalar do Porto

Oxford Brookes University

University of Bradford

INESC TEC

Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Field

[Title page iii]

Muhammad Younas Irfan Awan Filipe Portela

10.1109/ficloudw.2019.00002

Cite

Citations (0)

Pervasive and Intelligent Decision Support in Intensive Medicine – The Complete Picture

Lecture notes in computer science (2014)

Filipe Portela Manuel Filipe Santos José Machado António Abelha Álvaro Silva

10.1007/978-3-319-10265-8_9

Cite

Citations (52)

Improvements in Data Quality for Decision Support in Intensive Care

Electronic Healthcare (2011)

Filipe Portela Marta Vilas-Boas Manuel Filipe Santos

Nowadays, there is a plethora of technology in hospitals and, in particular, in intensive care units. The clinical data produced everyday can be integrated in a decision support system in real-time to improve quality of care of the critically ill patients. However, there are many sensitive aspects that must be taken into account, mainly the data quality and the integration of heterogeneous data sources. This paper presents INTCare, an Intelligent Decision Support System for Intensive Care in real-time and addresses the previous aspects, in particular, the development of an Electronic Nursing Record and the improvements in the quality of monitored data.

10.1007/978-3-642-23635-8_11

Cite

Citations (8)

Predicting Type of Delivery by Identification of Obstetric Risk Factors through Data Mining

Procedia Computer Science (2015)

Sónia Pereira Filipe Portela Manuel Filipe Santos José Machado António Abelha

In Maternity Care, a quick decision has to be made about the most suitable delivery type for the current patient. Guidelines are followed by physicians to support that decision; however, those practice recommendations are limited and underused. In the last years, caesarean delivery has been pursued in over 28% of pregnancies, and other operative techniques regarding specific problems have also been excessively employed. This study identifies obstetric and pregnancy factors that can be used to predict the most appropriate delivery technique, through the induction of data mining models using real data gathered in the perinatal and maternal care unit of Centro Hospitalar of Oporto (CHP). Predicting the type of birth envisions high-quality services, increased safety and effectiveness of specific practices to help guide maternity care decisions and facilitate optimal outcomes in mother and child. In this work was possible to acquire good results, achieving sensitivity and specificity values of 90.11% and 80.05%, respectively, providing the CHP with a model capable of correctly identify caesarean sections and vaginal deliveries.

Caesarean delivery

Identification

10.1016/j.procs.2015.08.573

Cite

Citations (43)

MULTI-MODEL AND PERVASIVE INTELLIGENT DECISION SUPPORT SYSTEM FOR UNIVERSITY APPLICATION

Tiago Augusto Magalhães Filipe Portela Manuel Filipe Santos

Source

Cite

Citations (1)

Towards a Pervasive Data Mining Engine—Architecture Overview

Advances in intelligent systems and computing (2016)

Rui Peixoto Filipe Portela Manuel Filipe Santos

Interface (matter)

10.1007/978-3-319-31307-8_58

Cite

Citations (6)

Predicting Triage Waiting Time in Maternity Emergency Care by Means of Data Mining

Advances in intelligent systems and computing (2016)

Sónia Pereira L. M. Torres Filipe Portela Manuel Filipe Santos José Machado

Triage

Cmin

10.1007/978-3-319-31307-8_60

Cite

Citations (2)

Predicting Preterm Birth in Maternity Care by Means of Data Mining

Lecture notes in computer science (2015)

Sónia Pereira Filipe Portela Manuel Filipe Santos José Machado António Abelha

Preterm labour

10.1007/978-3-319-23485-4_12

Cite

Citations (1)

Benefits of Bring Your Own Device in Healthcare

Advances in medical technologies and clinical practice book series (2017)

Filipe Portela Ailton Moreira Manuel Filipe Santos

Bring Your Own Device (BYOD) has become very popular topic in information technology because this approach allows the employees to bring their personal devices into organization and they want to use them to access the organization information. This trend has some benefits both for organization and to employees. This paper aims to identify those benefits as well the advantages and disadvantages of BYOD usage in organization. Also, it is present a SWOT analysis of BYOD usage. It is introduced an approach about BYOD in healthcare also. Utilizing personal devices at work is beneficial to organizational employees because they are in some way satisfies, and they have more freedom and choice to use their devices. This freedom and choice can easily lead the employees to be more productivity, flexibility. The organization who embraces BYOD policies found their employees happier, more productive, and more collaborative.

Telecommuting

10.4018/978-1-5225-2851-7.ch003

Cite

Citations (5)

Predicting Nosocomial Infection by Using Data Mining Technologies

Advances in intelligent systems and computing (2015)

Eva Silva Luciana Cardoso Filipe Portela António Abelha Manuel Filipe Santos

10.1007/978-3-319-16528-8_18

Cite

Citations (11)