Search AMIA.org

Biomedical text summarization helps biomedical information seekers avoid information overload by reducing the length of a document while preserving the contents' essence. Our systematic review investigates the most recent biomedical text summarization researches on biomedical literature and electronic health records by analyzing their techniques, areas of application, and evaluation methods. We identify gaps and propose potential directions for future research.

Clinical notes contain an abundance of important, but not-readily accessible, information about patients. Systems that automatically extract this information rely on large amounts of training data of which there exists limited resources to create. Furthermore, they are developed disjointly, meaning that no information can be shared among task-specific systems. This bottleneck unnecessarily complicates practical application, reduces the performance capabilities of each individual solution, and associates the engineering debt of managing [...]

A number of clinical decision support tools aim to use observational data to address immediate clinical needs, but few of them address challenges and biases inherent in such data. The goal of this article is to describe the experience of running a data consult service that generates clinical evidence in real time and characterize the challenges related to its use of observational data.

The study sought to investigate whether consistent use of the Veterans Health Administration's My HealtheVet (MHV) online patient portal is associated with improvement in diabetes-related physiological measures among new portal users.

We investigated the progression of healthcare cybersecurity over 2014-2019 as measured by external risk ratings. We further examined the relationship between hospital data breaches and cybersecurity ratings.

Substance use screening in adolescence is unstandardized and often documented in clinical notes, rather than in structured electronic health records (EHRs). The objective of this study was to integrate logic rules with state-of-the-art natural language processing (NLP) and machine learning technologies to detect substance use information from both structured and unstructured EHR data.

Differential privacy is a relatively new method for data privacy that has seen growing use due its strong protections that rely on added noise. This study assesses the extent of its awareness, development, and usage in health research.

The study sought to conduct a systematic review to explore the functions utilized by electronic cancer survivorship care planning interventions and assess their effects on patient and provider outcomes.