Using data mining for prediction of hospital length of stay: an application of the CRISP-DM Methodology

Hospitals are nowadays collecting vast amounts of data related with patient records. All this data hold valuable knowledge that can be used to improve hospital decision making. Data mining techniques aim precisely at the extraction of useful knowledge from raw data. This work describes an implementation of a medical data mining project approach based on the CRISP-DM methodology. Recent real-world data, from 2000 to 2013, were collected from a Portuguese hospital and related with inpatient hospitalization. The goal was to predict generic hospital Length Of Stay based on indicators that are commonly available at the hospitalization process (e.g., gender, age, episode type, medical specialty). At the data preparation stage, the data were cleaned and variables were selected and transformed, leading to 14 inputs. Next, at the modeling stage, a regression approach was adopted, where six learning methods were compared: Average Prediction, Multiple Regression, Decision Tree, Artificial Neural Network ensemble, Support Vector Machine and Random Forest. The best learning model was obtained by the Random Forest method, which presents a high quality coefficient of determination value (0.81). This model was then opened by using a sensitivity analysis procedure that revealed three influential input attributes: the hospital episode type, the physical service where the patient is hospitalized and the associated medical specialty. Such extracted knowledge confirmed that the obtained predictive model is credible and with potential value for supporting decisions of hospital managers.

Development of polymer wicks for the fabrication of bio-medical sensors

Polymer based wicking structures were fabricated by sintering powders of polycarbonate (PC), ultra-high molecular weight polyethylene and polyamide 12, aiming at selecting a suitable material for an innovative electroencephalography (EEG) bio-electrode. Preliminary experiments showed that PC based wicks displayed the best mechanical properties, therefore more detailed studies were carried out with PC to evaluate the influence of powder granulometry and processing parameters (pressure, temperature and time) on the mechanical properties, porosity, mean pore radius and permeability of the wicks. It was concluded that the mechanical properties are significantly enhanced by increasing the processing time and pressure, although at the expense of a significant decrease of porosity and mean pore diameter (and thus permeability), particularly for the highest applied pressures (74kPa). However, a good compromise between porosity/permeability and mechanical properties could be obtained by sintering PC powders of particle sizes below 500μm at 165°C for 5min, upon an applied pressure of 56kPa. Moreover, PC proved to be chemically stable in contact with an EEG common used disinfectant. Thus, wicking structures with appropriate properties for the fabrication of reusable bio-electrodes could be fabricated from the sintering of PC powders.

Variation of the physicochemical and morphological characteristics of solvent casted poly(vinylidene fluoride) along its binary phase diagram with dimethylformamide

Poly(vinylidene fluoride), PVDF, films and membranes were prepared by solvent casting from dimethylformamide, DMF, by systematically varying polymer/solvent ratio and solvent evaporation temperature. The effect of the processing conditions on the morphology, degree of porosity, mechanical and thermal properties and crystalline phase of the polymer were evaluated. The obtained microstructure is explained by the Flory-Huggins theory. For the binary system, the porous membrane formation is attributed to a spinodal decomposition of the liquid-liquid phase separation. The morphological features were simulated through the correlation between the Gibbs total free energy and the Flory-Huggins theory. This correlation allowed the calculation of the PVDF/DMF phase diagram and the evolution of the microstructure in different regions of the phase diagram. Varying preparation conditions allow tailoring polymer 2 microstructure while maintaining a high degree of crystallinity and a large β crystalline phase content. Further, the membranes show adequate mechanical properties for applications in filtration or battery separator membranes.

Otimização do internamento no Hospital de Braga usando metodologia Kaizen

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Engenharia Clínica)