Objective Employing transfer learning (TL) with convolutional neural networks (CNNs), well-
trained on non-medical ImageNet dataset, has shown promising results for medical image …

Importance In making decisions about patient care, clinicians raise questions and are
unable to pursue or find answers to most of them. Unanswered questions may lead to …

Objective The amount of information for clinicians and clinical researchers is growing
exponentially. Text summarization reduces information as an attempt to enable users to find …

The US health system has recently achieved widespread adoption of electronic health
record (EHR) systems, primarily driven by financial incentives provided by the Meaningful …

Objective To evaluate common data models (CDMs) to determine which is best suited for
sharing data from a large, longitudinal, electronic health record (EHR)-based community …

Objectives Patient-generated health data (PGHD) are clinically relevant data captured by
patients outside of the traditional care setting. Clinical use of PGHD has emerged as an …

To support clinical decision-making, computerized information retrieval tools known as
“infobuttons” deliver contextually-relevant knowledge resources into clinical information …

Abstract Objective The US Preventive Services Task Force (USPSTF) requires the
estimation of lifetime pack-years to determine lung cancer screening eligibility. Leading …

Community engagement is critical to accelerate and improve implementation of evidence-
based interventions to reduce health inequities. Community-engaged dissemination and …

Objectives Extracting data from publication reports is a standard process in systematic
review (SR) development. However, the data extraction process still relies too much on …