Escola Superior de Tecnologia e Gestão
Permanent URI for this community
Browse
Browsing Escola Superior de Tecnologia e Gestão by Author "Abelha, António"
Now showing 1 - 2 of 2
Results Per Page
Sort Options
- Knowledge discovery for pervasive and real-time intelligent decision support in intensive care medicinePublication . Portela, Filipe; Gago, Pedro; Santos, Manuel Filipe; Silva, Álvaro; Rua, Fernando; Machado, José Manuel; Abelha, António; Neves, JoséPervasiveness, real-time and online processing are important requirements included in the researchers’ agenda for the development of future generation of Intelligent Decision Support Systems (IDSS). In particular, knowledge discovery based IDSS operating in critical environments such of intensive care, should be adapted to those new requests. This paper introduces the way how INTCare, an IDSS developed in the intensive care unit of the Centro Hospitalar do Porto, will accommodate the new functionalities. Solutions are proposed for the most important constraints, e.g., paper based data, missing values, values out- of-range, data integration, data quality. The benefits and limitations of the approach are discussed.
- Resurgery Clusters in Intensive MedicinePublication . Peixoto, Ricardo; Portela, Filipe; Pinto, Filipe; Santos, Manuel Filipe; Machado, José; Abelha, António; Rua, FernandoThe field of critical care medicine is confronted every day with cases of surgical interventions. When Data Mining is properly applied in this field, it is possible through predictive models to identify if a patient, should or should not have surgery again upon the same problem. The goal of this work is to apply clustering techniques in collected data in order to categorize re-interventions in intensive care. By knowing the common characteristics of the re-intervention patients it will be possible to help the physician to predict a future resurgery. For this study various attributes were used related to the patient’s health problems like heart problems or organ failure. For this study it was also considered important aspects such as age and what type of surgery the patient was submitted. Classes were created with the patients’ age and the number of days after the first surgery. Another class was created where the type of surgery that the patient was operated upon was identified. This study comprised Davies Bouldin values between -0.977 and -0.416. The used variables, in addition to being provided by Hospital de Santo António in Porto, they are provided from the electronic medical record.