Optical chemical structure recognition is the problem of converting a bitmap image containing a chemical structure formula into a standard structured representation of the molecule. We introduce a novel approach to this problem based on the pipelined integration of pattern recognition techniques with probabilistic knowledge representation and reasoning. Basic entities and relations (such as textual elements, points, lines, etc.) are first extracted by a low-level processing module. A probabilistic reasoning engine based on Markov logic, embodying chemical and graphical knowledge, is subsequently used to refine these pieces of information. An annotated connection table of atoms and bonds is finally assembled and converted into a standard chemical exchange format. We report a successful evaluation on two large image data sets, showing that the method compares favorably with the current state-of-the-art, especially on degraded low-resolution images. The system is available as a web server at http://mlocsr.dinfo.unifi.it.
Recent advances in technology, information technology, Internet networks, and, more recently, fiber optics in industrialized countries allow the exchange of a huge amount of data, in real time, across the globe. The acquisition of increasingly sophisticated technologies has made it possible to develop telemedicine, by which the specialist’s evaluation can be carried out on the patient even remotely. In Italy, this very useful tool, although possible from a technological and information technology point of view, has not been developed because of the lack of clear and univocal rules and of major administrative obstacles related to the Italian Public Health System. To promote telemedicine implementation in Italy, the Italian Society of Clinical Neurophysiology and the Italian Society of Telemedicine together with the National Centre for Telemedicine and New Assistive Technologies of the Italian Higher Institute of Health prepared these inter-society recommendations. Because of potential forensic value of these recommendations, they were prepared considering the current regulations and the General Data Protection Regulation and will provide the basis for a Consensus Conference planned to discuss and prepare National Telemedicine Guidelines.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.