Improving the Prescription Process Information Support with Structured Medical Prospectuses Using Neural Networks.

To provide the best treatment, a physician needs information about both the patient and the medicines matching the patient status and improving it. In this article, we present three methods for structuring the sections of medical prospectuses using neural networks. To structure the information from a medical prospectus we use 3 web sources with structured data from sections (with names sections from prospectuses and with uniformized names of sections) to train as input for neural networks.

Named Entity Recognition and Classification for Medical Prospectuses.

Structuring and processing natural language is a growing challenge in the medical field. Researchers are looking for new ways to extract knowledge to create databases and applications to help doctors treat patients and minimize medical errors. A very important part in treating a patient is to provide a fair and effective treatment for diseases.

Harnessing Ontologies to Improve Prescription in Pediatric Medicine.

There are many drug databases, but sometimes the data quality may result in wrong medication for patients. Results that it is very important to provide a good quality drug information, supply structured information and build useful relations between the drugs related information and the patient status in terms of particularities. Children are the most sensitive to drug dosage or certain substances that is why pediatrics was our first choice for the research.