Digital therapeutics (DTx) promises to make healthcare more accessible, proactive, and patient-centered, empowering patients, while also giving clinicians the ability to make better diagnoses. To better understand DTx, Michelle Louise Jose, a healthtech pharmacist who prepares natural language processing content, explains how one must first examine the key differences between telemedicine and DTx, as well as the challenges that must be addressed for DTx to fulfill its potential.

The Ubiquitous Pharmacogenomics (U-PGx) consortium has launched the U-PGx project in an effort to overcome existing barriers and deficiencies in healthcare systems and health infrastructure so as to establish a clinical decision support framework to deliver care that is more personalized and cost-effective, adaptable and able to be implemented in many countries, regardless of language, infrastructure, and healthcare system characteristics.

Debate swirls about how natural language processing can help advance artificial intelligence in the healthcare sector, where most data are unstructured. Jan Sevcik takes a closer look at NLP, the analysis of unstructured text, and how to understand its strategy.

Talking machines are not simply good for films, they can save millions of lives argues Satyen K. Bordoloi, recounting both the history and, more importantly, the future of cognitive computing.

Computational linguist Janna Lipenkova discusses how trending topics in the media can be extracted using natural language processing by looking at prominent time series patterns, analyzing the meaning of a topic by constructing and inspecting its semantic context, and witnessing changes over time in the semantic context of a topic.