clinical decision support | Digital Health

Lederman A, Lederman R, Verspoor K. Tasks as needs: reframing the paradigm of clinical natural language processing research for real-world decision support, Journal of the American Medical Informatics Association, Volume 29, Issue 10, October 2022, Pages 1810–1817, https://doi.org/10.1093/jamia/ocac121

Tasks as needs: reframing the paradigm of clinical natural language processing research for real-world decision support. Electronic medical records are increasingly used to store patient information in hospitals and other clinical settings. There has been a corresponding proliferation of clinical natural language processing (cNLP) systems aimed at using text data in these records to improve clinical

Artificial Intelligence in Clinical Decision Support

Challenges for Evaluating AI and Practical Implications Artificial intelligence (AI) promises to transform clinical decision-making processes as it has the potential to harness the vast amounts of genomic, biomarker, and phenotype data that is being generated across the health system including from health records and delivery systems, to improve the safety and quality of care

Pederson M, Verspoor K, Jenkinson M, Law M, Abbott DF, Jackson GD (2020). Artificial Intelligence for clinical decision support in neurology. Brain Communications.

Artificial intelligence is one of the most exciting methodological shifts in our era. It holds the potential to transform healthcare as we know it, to a system where humans and machines work together to provide better treatment for our patients. It is now clear that cutting edge artificial intelligence models in conjunction with high-quality clinical

Coiera E, Kocaballi AB, Halamka J, Laranjo L. The digital scribe. npj Digital Medicine. 2018; 1(1):58.

Current generation electronic health records suffer a number of problems that make them inefficient and associated with poor clinical satisfaction. Digital scribes or intelligent documentation support systems, take advantage of advances in speech recognition, natural language processing and artificial intelligence, to automate the clinical documentation task currently conducted by humans. Whilst in their infancy, digital