Search AMIA.org

To present clinicians at the point-of-care with real-world data on the effectiveness of various treatment options in a precision cohort of patients closely matched to the index patient.

The study sought to develop and empirically validate an integrative situational privacy calculus model for explaining potential users' privacy concerns and intention to install a contact tracing mobile application (CTMA).

To apply natural language processing (NLP) techniques to identify individual events and modes of communication between healthcare professionals and families of critically ill patients from electronic medical records (EMR).

The study sought to describe the contributions of clinical informatics (CI) fellows to their institutions' coronavirus disease 2019 (COVID-19) response.

Large clinical databases are increasingly used for research and quality improvement. We describe an approach to data quality assessment from the General Medicine Inpatient Initiative (GEMINI), which collects and standardizes administrative and clinical data from hospitals.

We sought to demonstrate the feasibility of utilizing deep learning models to extract safety signals related to the use of dietary supplements (DSs) in clinical text.

The study sought to test the possibility of differentiating chest x-ray images of coronavirus disease 2019 (COVID-19) against other pneumonia and healthy patients using deep neural networks.

Estimating the hospitalization risk for people with comorbidities infected by the SARS-CoV-2 virus is important for developing public health policies and guidance. Traditional biostatistical methods for risk estimations require: (i) the number of infected people who were not hospitalized, which may be severely undercounted since many infected people were not tested; (ii) comorbidity information for people not hospitalized, which may not always be readily available. We aim to overcome these [...]

Our goal is to summarize the collective experience of 15 organizations in dealing with uncoordinated efforts that result in unnecessary delays in understanding, predicting, preparing for, containing, and mitigating the COVID-19 pandemic in the US. Response efforts involve the collection and analysis of data corresponding to healthcare organizations, public health departments, socioeconomic indicators, as well as additional signals collected directly from individuals and communities. We focused on electronic health record [...]