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[This corrects the article DOI: 10.1093/jamiaopen/ooac113.].

A shallow convolutional neural network (CNN), TextCNN, has become nearly ubiquitous for classification among clinical and medical text. This research presents a novel eXplainable-AI (X-AI) software, Red Flag/Blue Flag (RFBF), designed for binary classification with TextCNN. RFBF visualizes each convolutional filter's discriminative capability. This is a more informative approach than direct assessment of logit contribution, features that overfit to train set nuances on smaller datasets may indiscriminately activate large logits [...]

The aim of this study was to test the feasibility of PICO (participants, interventions, comparators, outcomes) entity extraction using weak supervision and natural language processing.

Tumor registries are a rich source of real-world data which can be used to test important hypotheses that inform clinical care. Exploratory data analysis at the level of individual subjects, when enhanced by interactive data visualizations, has the potential to provide novel insights and generate new hypothesis.

A connected system with smart devices could transform patient care and empower patients control of their asthma.

In response to the coronavirus disease 2019 (COVID-19) pandemic, the Veterans Health Administration (VA) rapidly expanded virtual care (defined as care delivered by video and phone), raising concerns about technology access disparities (ie, the digital divide). Virtual care was somewhat established in primary care and mental health care prepandemic, but video telehealth implementation was new for most subspecialties, including cardiology. We sought to identify patient characteristics of virtual and video-based [...]

[This corrects the article DOI: 10.1093/jamiaopen/ooac036.].

Mapping internal, locally used lab test codes to standardized logical observation identifiers names and codes (LOINC) terminology has become an essential step in harmonizing electronic health record (EHR) data across different institutions. However, most existing LOINC code mappers are based on text-mining technology and do not provide robust multi-language support.

This study aims to investigate key considerations and critical factors that influence the implementation and adoption of smart glasses in fast-paced medical settings such as emergency medical services (EMS).

To evaluate the feasibility, accuracy, and interoperability of a natural language processing (NLP) system that extracts diagnostic assertions of pneumonia in different clinical notes and institutions.