Free or low-cost sources of unstructured information, such as Internet news and online discussion sites, provide detailed local and near real-time data on disease outbreaks, even in countries that lack traditional public health surveillance. To improve public health surveillance and, ultimately, interventions, we examined 3 primary systems that process event-based outbreak information: Global Public Health Intelligence Network, HealthMap, and EpiSPIDER. Despite similarities among them, these systems are highly complementary because they monitor different data types, rely on varying levels of automation and human analysis, and distribute distinct information. Future development should focus on linking these systems more closely to public health practitioners in the field and establishing collaborative networks for alert verification and dissemination. Such development would further establish event-based monitoring as an invaluable public health resource that provides critical context and an alternative to traditional indicator-based outbreak reporting.
ITK is a powerful open-source toolkit implementing state-of-the-art algorithms in medical image processing and analysis. MATLAB, on the other hand, is well-known for its easy-to-use, powerful prototyping capabilities that significantly improve productivity. With the help of MATITK, biomedical image computing researchers familiar with MATLAB can harness the power of ITK algorithms while avoiding learning C++ and dealing with low-level programming issues.
H. Digabel, и C. Lantuéjoul. Actes du Second Symposium Europeen d'Analyse Quantitative des Microstructures en Sciences des Materiaux, Biologie et Medecine, стр. 85-99. (4-7 10 1978)