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Register a new userModeling National Trends on Health in the Philippines Using ARIMA
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Added by
Florence Jean Talirongan
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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Health is a very important prerequisite in peoples well-being and happiness. Several studies were more focused on presenting the occurrence on specific disease like forecasting the number of dengue and malaria cases. This paper utilized the time series data for trend analysis and data forecasting using ARIMA model to visualize the trends of health data on the ten leading causes of deaths, leading cause of morbidity and leading cause of infants deaths particularly in the Philippines presented in a tabular data. Figures for each disease trend are presented individually with the use of the GRETL software. Forecasting results of the leading causes of death showed that Diseases of the heart, vascular system, accidents, Chronic lower respiratory diseases and Chronic Tuberculosis (all forms) showed a slight changed of the forecasted data, Malignant neoplasms showed unstable behavior of the forecasted data, and Pneumonia, diabetes mellitus, Nephritis, nephrotic syndrome and nephrosis and certain conditions originating in perinatal showed a decreasing patterns based on the forecasted data.
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Large-scale national level Personal Health Record (PHR) has been implemented in Australia. However, usability, data quality and poor functionalities have resulted in low utility affecting enrollment and participation rates by both patients and clinicians alike. Development of new applications deriving secondary utility of data can enhance use of PHRs but there is limited understanding on processes involved in development of third-party applications with nationally run PHRs. This paper prsents an analysis of processes and regulatory requirements for developing applications of data from My Health Record, Australian nationally run PHR and subsequently implementation of a patient oriented software application using data sourced from My Health Record.
This study analyzes patterns of physical, mental, lifestyle, and personality factors in college students in different periods over the course of a semester and models their relationships with students academic performance. The data analyzed was collected through smartphones and Fitbit. The use of machine learning models derived from the gathered data was employed to observe the extent of students behavior associated with their GPA, lifestyle, physical health, mental health, and personality attributes. A mutual agreement method was used in which rather than looking at the accuracy of results, the model parameters and weights of features were used to find common behavioral trends. From the results of the model creation, it was determined that the most significant indicator of academic success defined as a higher GPA, was the places a student spent their time. Lifestyle and personality factors were deemed more significant than mental and physical factors. This study will provide insight into the impact of different factors and the timing of those factors on students academic performance.
This study reported the conference papers presented conducted by the two computing societies in the Philippines. Toward this goal, all published conference proceedings from the National Conference of IT Education and Philippine Computing Society Conference were gathered and analyzed using social network analysis. The findings of the study disclosed that there are 733 papers presented in the conference for the span of 18 years. On the average, both conferences had 27 papers presented annually. Private higher education institutions dominated the list of research productive schools where De La Salle University tops the list. A researcher in the University of the Philippines-Diliman is the most prolific researcher with 39 publications and algorithm was the most researched topic. Researchers tend to work in small team consisting of 2 to 3 members. Implications and limitations of the study are also presented.
Indian voters from Kashmir to Kanyakumari select their representatives to form their parliament by going to polls. Indias election is one of the largest democratic exercise in the world history. About 850 million eligible voters determine which political party or alliance will form the government and in turn, will serve as prime minister. Given the electoral rules of placing a polling place within 2 kilometers of every habitation, it comes as no surprise that is indeed a humongous task for the Election Commission of India (ECI). It sends around 11 million election workers through tough terrains to reach the last mile. This exercise also comes as ever growing expenditure for the ECI. This paper proposes the use of Automated Teller Machines (ATM) and Point Of Sale (POS) machines to be used to cover as much as urban, rural and semi-urban places possible given the wide network of National Financial Switch (NFS) and increase in connectivity through Digital India initiative. This would add to the use of the existing infrastructure to accommodate a free, fair and transparent election.
India accounts for 11% of maternal deaths globally where a woman dies in childbirth every fifteen minutes. Lack of access to preventive care information is a significant problem contributing to high maternal morbidity and mortality numbers, especially in low-income households. We work with ARMMAN, a non-profit based in India, to further the use of call-based information programs by early-on identifying women who might not engage on these programs that are proven to affect health parameters positively.We analyzed anonymized call-records of over 300,000 women registered in an awareness program created by ARMMAN that uses cellphone calls to regularly disseminate health related information. We built robust deep learning based models to predict short term and long term dropout risk from call logs and beneficiaries demographic information. Our model performs 13% better than competitive baselines for short-term forecasting and 7% better for long term forecasting. We also discuss the applicability of this method in the real world through a pilot validation that uses our method to perform targeted interventions.
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