Focus Issue Archive

In 2015, the White House and the National Institutes of Health announced the inception of the All of Us Research Program “to bring us closer to curing diseases like cancer and diabetes, and to give each of us access to the personalized information we need to keep ourselves and our families healthier.” Now approaching the first decade, the vision to enhance innovation in biomedical research remains strong with the goal of moving the United States into an era where medical treatment and other health interventions can be tailored to individuals.

There is no doubt that there is a need for wide-scale adoption and implementation of policies that support firearm injury risk detection and prevention. However, innovative health informatics and data science approaches have a role to play in this growing public health crisis.

This Focus Issue focuses on how the reported work addresses return of value to communities.

The 2023 Annual Report from the Johns Hopkins Center for Gun Violence Solutions reports an analysis of the 2021 firearm fatality data released from the Centers for Disease Control and Prevention in January of 2023.

There is no doubt that there is a need for wide-scale adoption and implementation of policies that support firearm injury risk detection and prevention. However, innovative health informatics and data science approaches have a role to play in this growing public health crisis.

Large Language Models (LLMs) are a type of generative Artificial Intelligence (AI) that is specifically focused on generating natural language text. These models are trained on massive amounts of text data and use deep learning algorithms to generate new text that is often indistinguishable from human-generated text.
This Focus Issue focuses on the intersection of biomedicine/health and LLMs.

The onset of the COVID-19 pandemic spurred innovation in the development and accelerated adoption of remote tools for clinical care (i.e., telehealth) and research. There is an opportunity to blend remote, hybrid, and in-person approaches to gain inclusive perspectives for human-centered design of health data visualizations. Designing for lay audiences is inherently challenging because their needs are often not well-articulated and their requests may even violate basic design principles. Methods that work well for domain experts (e.g., clinicians) may not be appropriate for lay audiences.
This Focus Issue brings together best practices across informatics, human factors, human computer interaction, cognitive science, data science, and computer science to develop visualizations that are inclusive of and informed by the target audience's needs.

With the advent of computerization in healthcare, sustained efforts to develop standardized nursing terminologies since the 1970’s have enabled nursing assessments and care to be included in electronic health records as a reliable and valid means to determine the value of nursing care on patient outcomes.
This Focus Issue looks at the role of standardized nursing terminologies and supporting semantic interoperability standards in advancing quality of care, population health, and health equity across the care continuum