Journal of biomedical informatics
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Mobile technologies are a useful platform for the delivery of health behavior interventions. Yet little work has been done to create a rigorous and standardized process for the design of mobile health (mHealth) apps. This project sought to explore the use of the Information Systems Research (ISR) framework as guide for the design of mHealth apps. ⋯ Use of the ISR framework is a potentially useful approach for the design of a mobile app that incorporates end-users' design preferences.
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Amyotrophic Lateral Sclerosis (ALS) is a devastating disease and the most common neurodegenerative disorder of young adults. ALS patients present a rapidly progressive motor weakness. This usually leads to death in a few years by respiratory failure. ⋯ Experimental results show an area under the receiver operating characteristics curve (AUC) in the test set of approximately 79% for time windows of 90, 180 and 365 days. Creating patient snapshots using hierarchical clustering with constraints outperforms the state of the art, and the proposed prognostic model becomes the first non population-based approach for prognostic prediction in ALS. The results are promising and should enhance the current clinical practice, largely supported by non-standardized tests and clinicians' experience.
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To develop multivariate vector-ARMA (VARMA) forecast models for predicting emergency department (ED) demand in Western Australia (WA) and compare them to the benchmark univariate autoregressive moving average (ARMA) and Winters' models. ⋯ VARMA models are a reliable forecasting method to predict ED demand for strategic planning and resource allocation. While the ARMA models are a closely competing alternative, they under-estimated future ED demand.
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Youth are prolific users of cell phone minutes and text messaging. Numerous programs using short message service text messaging (SMS) have been employed to help improve health behaviors and health outcomes. However, we lack information on whether and what type of interaction or engagement with SMS program content is required to realize any benefit. ⋯ The first two months of the program in each year had the highest response frequency. An important next step is to assess whether higher response to SMS results in greater efficacy. This future work can facilitate greater attention to message design and content to ensure messages are engaging for the intended audience.
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Although potential drug-drug interactions (PDDIs) are a significant source of preventable drug-related harm, there is currently no single complete source of PDDI information. In the current study, all publically available sources of PDDI information that could be identified using a comprehensive and broad search were combined into a single dataset. The combined dataset merged fourteen different sources including 5 clinically-oriented information sources, 4 Natural Language Processing (NLP) Corpora, and 5 Bioinformatics/Pharmacovigilance information sources. ⋯ In spite of the low degree of overlap, several dozen cases were identified where PDDI information provided in drug product labeling might be augmented by the merged dataset. Moreover, the combined dataset was also shown to improve the performance of an existing PDDI NLP pipeline and a recently published PDDI pharmacovigilance protocol. Future work will focus on improvement of the methods for mapping between PDDI information sources, identifying methods to improve the use of the merged dataset in PDDI NLP algorithms, integrating high-quality PDDI information from the merged dataset into Wikidata, and making the combined dataset accessible as Semantic Web Linked Data.