Application of natural language processing techniques to identify off-label drug usage from various online health communities.

Objective: Outcomes mentioned on online health communities (OHCs) by patients can serve as a source of evidence for off-label drug usage evaluation, but identifying these outcomes manually is tedious work. We have built a natural language processing model to identify off-label usage of drugs mentioned in these patient posts.

Materials And Methods: Single patient posts from 4 major OHCs were considered for this study.

New insight into the synthesis, morphological architectures and biomedical applications of elemental selenium nanostructures.

Selenium nanoparticles have been shown to be versatile in their applications by being used in catalysis, solar cells, electronic devices and especially in medical applications such as antiviral, anticancer, antitumor and antibacterial agents in different concentrations. They have also shown enhanced drug and gene delivery by conjugating with drug molecules and showing high synergistic effects. After realising their usefulness in the biomedical field, we have made a sincere effort to correlate and consolidate the recent developments made in their synthesis methods, structural features and biological applications.