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Ateneo de Manila University

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Articles 31 - 34 of 34

Full-Text Articles in Databases and Information Systems

Towards Developing An Intelligent Agent To Assist In Patient Diagnosis Using Neural Networks On Unstructured Patient Clinical Notes: Initial Analysis And Models, Ma. Regina Justina E. Estuar, Christian E. Pulmano Jan 2016

Towards Developing An Intelligent Agent To Assist In Patient Diagnosis Using Neural Networks On Unstructured Patient Clinical Notes: Initial Analysis And Models, Ma. Regina Justina E. Estuar, Christian E. Pulmano

Department of Information Systems & Computer Science Faculty Publications

Technological advances in information-communication technologies in the health ecosystem have allowed for the recording and consumption of massive amounts of structured and unstructured health data. In developing countries, the use of Electronic Medical Records (EMR) is necessary to address the need for efficient delivery of services and informed decision-making, especially at the local level where health facilities and practitioners may be lacking. Text mining is a variation of data mining that tries to extract non-trivial information and knowledge from unstructured text. This study aims to determine the feasibility of integrating an intelligent agent within EMRs for automatic diagnosis prediction based …


Towards An Infodemiological Algorithm For Classification Of Filipino Health Tweets, Ma. Regina Justina E. Estuar, Kennedy E. Espina, Delfin Jay Sabido Ix, Raymond Josef Edward Lara, Vikki Car De Los Reyes Jan 2016

Towards An Infodemiological Algorithm For Classification Of Filipino Health Tweets, Ma. Regina Justina E. Estuar, Kennedy E. Espina, Delfin Jay Sabido Ix, Raymond Josef Edward Lara, Vikki Car De Los Reyes

Department of Information Systems & Computer Science Faculty Publications

Finding innovative ICT solutions to enhance the Philippines’ health sector is part and parcel of the Philippine eHealth Strategic Framework and Plan 2020 program. This study sees the opportunity of using collected Twitter data to create a model that processes tweets to produce a dataset that may be relevant in the field of epidemiology and infodemiology. Through the collection of relevant tweets, future studies may make use of the output of this research for various purposes, such as the improvement of epidemiological systems of the Department of Health in support of the eHealth strategy. In this study, we …


Designing Mobile Educational Games On Voter‟S Education: A Tale Of Three Engines, Ma. Regina Justina E. Estuar, Nadia Rowena C. Leetian, Michael B. Syson Oct 2013

Designing Mobile Educational Games On Voter‟S Education: A Tale Of Three Engines, Ma. Regina Justina E. Estuar, Nadia Rowena C. Leetian, Michael B. Syson

Department of Information Systems & Computer Science Faculty Publications

The rapid growth of mobile learning is influenced by the ability to access learning content anytime and anywhere. The on demand capability is available because mobile devices allow for convergence of internet and communications technologies. At the same time, the availability of engines makes development of mobile applications faster and seamless. However, not all mobile development engines are alike. This paper discusses on the development of mobile learning applications using mobile development engines in teaching Filipinos on responsible voting. Specifically, this paper discusses how AndEngine, Ren’Py, and homegrown Usbong were used to develop a mobile board game and a mobile …


Comparative Analysis Of Combinations Of Dimension Reduction And Data Mining Techniques For Malware Detection, Proceso L. Fernandez Jr, Jeffrey C. Yiu, Paul Albert R. Arana Oct 2010

Comparative Analysis Of Combinations Of Dimension Reduction And Data Mining Techniques For Malware Detection, Proceso L. Fernandez Jr, Jeffrey C. Yiu, Paul Albert R. Arana

Department of Information Systems & Computer Science Faculty Publications

Many malware detectors utilize data mining techniques as primary tools for pattern recognition. As the number of new and evolving malware continues to rise, there is an increasing need for faster and more accurate detectors. However, for a given malware detector, detection speed and accuracy are usually inversely related. This study explores several configurations of classification combined with feature selection. An optimization function involving accuracy and processing time is used to evaluate each configuration. A real data set provided by Trend Micro Philippines is used for the study. Among 18 di↵erent configurations studied, it is shown that J4.8 without feature …