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Editorial: Human-centered AI at work: common ground in theories and methods.
Front Artif Intell
April 2024
Department of Psychology, University of Lübeck, Lübeck, Germany.
Team-based care of the thoracic surgical patient.
Curr Opin Anaesthesiol
February 2024
Department of Anesthesiology and Critical Care, Orleans Street, Baltimore, Maryland, USA.
Purpose Of Review: Although team-based care has been shown in many sectors to improve outcomes, very little work has been done with the thoracic surgical patient. This review article focuses on this and, extrapolating from other closely related surgical fields, teamwork in thoracic surgery will be reviewed for outcome efficacy and substance.
Recent Findings: The optimal team has been shown to display behaviors that allow them to model future needs, predict disaster, be adaptable to change, and promote team cohesiveness all with a positive effect on perioperative outcome.
Human-AI teams-Challenges for a team-centered AI at work.
Front Artif Intell
September 2023
Robotics Research Group, Faculty of Mathematics and Computer Science, University of Bremen, Bremen, Germany.
As part of the Special Issue topic "Human-Centered AI at Work: Common Ground in Theories and Methods," we present a perspective article that looks at human-AI teamwork from a team-centered AI perspective, i. e., we highlight important design aspects that the technology needs to fulfill in order to be accepted by humans and to be fully utilized in the role of a team member in teamwork.
View Article and Find Full Text PDFBuilding Bridges Instead of Putting Up Walls: Connecting the "Teams" to Improve Soccer Players' Support.
Sports Med
December 2023
Faculty of Sport, Center for Research, Education, Innovation, and Intervention in Sport (CIFI2D), University of Porto, Porto, Portugal.
The increase in the economic value of soccer occurred in parallel with an increase in competing demands. Therefore, clubs and federations evolved to greater specialization (e.g.
View Article and Find Full Text PDFWhere Is the Digitally Silent Provider? Development and Validation of a Team-Centered Electronic Health Record Attribution Model for Supervising Residents.
Acad Med
January 2023
G. Rosenbluth is professor, Department of Pediatrics, and director of quality and safety programs, Office of Graduate Medical Education, University of California, San Francisco, San Francisco, California.
Problem: Providing trainees with data and benchmarks on their own patient populations is an Accreditation Council for Graduate Medical Education core residency requirement. Leveraging electronic health records (EHRs) for this purpose relies on correctly attributing patients to the trainees responsible for their care. EHR activity logs are useful for attributing interns to inpatients but not for attributing supervising residents, who often have no inpatient EHR usage obligations, and therefore may generate no digital "footprints" on a given patient-day from which to ascertain attribution.
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