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To assess the overlap of information between electronic health record (EHR) and patient-nurse verbal communication in home healthcare (HHC).

To review through an ethics lens the state of research in clinical natural language processing (NLP) for the study of bias and fairness, and to identify gaps in research.

Despite artificial intelligence (AI) being used increasingly in healthcare, implementation challenges exist leading to potential biases during the clinical decision process of the practitioner. The interaction of AI with novice clinicians was investigated through an identification task, an important component of diagnosis, in dental radiography. The study evaluated the performance, efficiency, and confidence level of dental students on radiographic identification of furcation involvement (FI), with and without AI assistance.

Develop and implement a prescription opioid registry in 10 diverse health systems across the US and describe trends in prescribed opioids between 2012 and 2018.

Facilitate the multi-appointment scheduling problems (MASPs) characteristic of longitudinal clinical research studies. Additional goals include: reducing management time, optimizing clinical resources, and securing personally identifiable information.

New York City (NYC) experienced a large first wave of coronavirus disease 2019 (COVID-19) in the spring of 2020, but the Health Department lacked tools to easily visualize and analyze incoming surveillance data to inform response activities. To streamline ongoing surveillance, a group of infectious disease epidemiologists built an interactive dashboard using open-source software to monitor demographic, spatial, and temporal trends in COVID-19 epidemiology in NYC in near real-time for [...]

The objective of this study is to understand the primary topics of consumer discussion on Twitter associated with telehealth for mental health or substance abuse for prepandemic versus during-pandemic time-periods, using a state-of-the-art machine learning (ML) natural language processing (NLP) method.

Clinical evidence logic statements (CELS) are shareable knowledge artifacts in a semistructured "If-Then" format that can be used for clinical decision support systems. This project aimed to assess factors facilitating CELS representation.

Improving health data interoperability through application programming interfaces (APIs) is a focus of US policy initiatives and could have tremendous impact on many aspects of care delivery, such as innovation, operational efficiency, and patient-centered care. To better understand the landscape of API use cases, we interviewed US thought leaders involved in developing and implementing standard-based APIs.

Reproducibility in medical research has been a long-standing issue. More recently, the COVID-19 pandemic has publicly underlined this fact as the retraction of several studies reached out to general media audiences. A significant number of these retractions occurred after in-depth scrutiny of the methodology and results by the scientific community. Consequently, these retractions have undermined confidence in the peer-review process, which is not considered sufficiently reliable to generate trust in [...]