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http://dx.doi.org/10.1016/j.jtcvs.2021.02.039 | DOI Listing |
Transl Behav Med
January 2025
Slone Epidemiology Center at Boston University, 72 E Concord St, Boston, MA, USA.
Artificial intelligence (AI) and its subset, machine learning, have tremendous potential to transform health care, medicine, and population health through improved diagnoses, treatments, and patient care. However, the effectiveness of these technologies hinges on the quality and diversity of the data used to train them. Many datasets currently used in machine learning are inherently biased and lack diversity, leading to inaccurate predictions that may perpetuate existing health disparities.
View Article and Find Full Text PDFFront Med (Lausanne)
January 2025
Clinical Informatics Fellowship Program, Baylor Scott & White Health, Round Rock, TX, United States.
Generative artificial intelligence (GenAI) is rapidly transforming various sectors, including healthcare and education. This paper explores the potential opportunities and risks of GenAI in graduate medical education (GME). We review the existing literature and provide commentary on how GenAI could impact GME, including five key areas of opportunity: electronic health record (EHR) workload reduction, clinical simulation, individualized education, research and analytics support, and clinical decision support.
View Article and Find Full Text PDFNurs Leadersh (Tor Ont)
June 2025
Clinical Practice Leader Corporate Interprofessional Practice Lakeridge Health Durham Region, ON.
The integration of artificial intelligence (AI) into healthcare represents a paradigm shift with the potential to enhance patient care and streamline clinical operations. This commentary explores the Canadian perspective on key organizational considerations for nurse executives, emphasizing the critical role they play in fostering the establishment of AI governance structures and advancing the front-line adoption of AI in nursing practice. The discussion delves into five domains of consideration, analyzing recent developments and implications for nursing executives.
View Article and Find Full Text PDFTomography
January 2025
Department of Radiology, University of Padova, 35127 Padova, Italy.
This commentary examines Topological Data Analysis (TDA) in radiology imaging, highlighting its revolutionary potential in medical image interpretation. TDA, which is grounded in mathematical topology, provides novel insights into complex, high-dimensional radiological data through persistent homology and topological features. We explore TDA's applications across medical imaging domains, including tumor characterization, cardiovascular imaging, and COVID-19 detection, where it demonstrates 15-20% improvements over traditional methods.
View Article and Find Full Text PDFERJ Open Res
January 2025
Copenhagen Academy for Medical Education and Simulation, Rigshospitalet, The Capital Region of Denmark, Copenhagen, Denmark.
Rationale: Flexible bronchoscopy is an operator-dependent procedure. An automatic bronchial identification system based on artificial intelligence (AI) could help bronchoscopists to perform more complete and structured procedures through automatic guidance.
Methods: 101 participants were included from six different continents at the European Respiratory Society annual conference in Milan, 9-13 September 2023.
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