Effectiveness of the Philippine Stock Exchange Index (PSEi) as training dataset in forecasting Philippine stock prices using neural networks

The health of the stock market is considered critical to a country’s economic development. The volatility of stock prices which are influenced by inflation rates, interest rates, tax changes, and other monetary policies, makes the prediction and analysis a very challenging task. With the use of advanced intelligent techniques such as deep learning, we can improve stock market prediction. In this study, we investigate the effectiveness of using the Philippine Stock Exchange index (PSEi) as a training dataset of three artificial neural networks (ANNs), namely, Multilayer Perceptron (MLP), Long-Short Term Memory (LSTM), and Convolutional Neural Network (CNN) in forecasting the daily closing prices of local stocks AbaCore Capital Holdings, Inc. (ABA) and San Miguel Corporation (SMC). Based on the mean squared error (MSE) and mean absolute percentage error (MAPE), the models using MLP with the activation function of hyperbolic tangent (tanh) are the suitable neural network model for both ABA and SMC

The surgical safety checklist and patient outcomes after surgery: a prospective observational cohort study, systematic review and meta-analysis

© 2017 British Journal of Anaesthesia Background: The surgical safety checklist is widely used to improve the quality of perioperative care. However, clinicians continue to debate the clinical effectiveness of this tool. Methods: Prospective analysis of data from the International Surgical Outcomes Study (ISOS), an international observational study of elective in-patient surgery, accompanied by a systematic review and meta-analysis of published literature. The exposure was surgical safety checklist use. The primary outcome was in-hospital mortality and the secondary outcome was postoperative complications. In the ISOS cohort, a multivariable multi-level generalized linear model was used to test associations. To further contextualise these findings, we included the results from the ISOS cohort in a meta-analysis. Results are reported as odds ratios (OR) with 95% confidence intervals. Results: We included 44 814 patients from 497 hospitals in 27 countries in the ISOS analysis. There were 40 245 (89.8%) patients exposed to the checklist, whilst 7508 (16.8%) sustained ≥1 postoperative complications and 207 (0.5%) died before hospital discharge. Checklist exposure was associated with reduced mortality [odds ratio (OR) 0.49 (0.32–0.77); P\u3c0.01], but no difference in complication rates [OR 1.02 (0.88–1.19); P=0.75]. In a systematic review, we screened 3732 records and identified 11 eligible studies of 453 292 patients including the ISOS cohort. Checklist exposure was associated with both reduced postoperative mortality [OR 0.75 (0.62–0.92); P\u3c0.01; I2=87%] and reduced complication rates [OR 0.73 (0.61–0.88); P\u3c0.01; I2=89%). Conclusions: Patients exposed to a surgical safety checklist experience better postoperative outcomes, but this could simply reflect wider quality of care in hospitals where checklist use is routine