The recent advances at hardware level and the increasing requirement of personalization of care associated with the urgent needs of value creation for the patients has helped Artificial Intelligence (AI) to promote a significant paradigm shift in the most diverse areas of medical knowledge, particularly in Cardiology, for its ability to support decision-making and improve diagnostic and prognostic performance. In this context, the present work does a non-systematic review of the main papers published on AI in Cardiology, focusing on its main applications, potential impacts and challenges.
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http://dx.doi.org/10.36660/abc.20180431 | DOI Listing |
J Health Organ Manag
January 2025
University of Malta, Msida, Malta.
Purpose: This study explores how corporate social responsibility (CSR) and artificial intelligence (AI) can be combined in the healthcare industry during the post-COVID-19 recovery phase. The aim is to showcase how this fusion can help tackle healthcare inequalities, enhance accessibility and support long-term sustainability.
Design/methodology/approach: Adopting a viewpoint approach, the study leverages existing literature and case studies to analyze the intersection of CSR and AI.
BMC Oral Health
January 2025
Department of Stomatology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, China.
Background: Proper torque control is crucial to the outcome of orthodontic treatment. This study aimed to employ finite element analysis to compare the torque capabilities of a novel spherical self-ligating bracket with a lock-hook system against those of commonly used passive self-ligating and conventional bracket systems, as well as to reveal the biomechanical changes in the periodontal ligament (PDL) during torque expression.
Methods: A maxillary right central incisor, along with its PDL and alveolar bone, were modeled.
BMC Med Educ
January 2025
Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Ordu University, Ordu, 52200, Turkey.
Introduction: Artificial intelligence (AI) has gained significant attention in dentistry due to its potential to revolutionize practice and improve patient outcomes. However, dentists' views and attitudes toward technology can affect the application of AI. This perception and attitude can be affected by the personality traits of individuals.
View Article and Find Full Text PDFBMC Med Inform Decis Mak
January 2025
QUEST Center for Responsible Research, Berlin Institute of Health at Charité Universitätsmedizin Berlin, Berlin, Germany.
Background: Machine learning (ML) is increasingly used to predict clinical deterioration in intensive care unit (ICU) patients through scoring systems. Although promising, such algorithms often overfit their training cohort and perform worse at new hospitals. Thus, external validation is a critical - but frequently overlooked - step to establish the reliability of predicted risk scores to translate them into clinical practice.
View Article and Find Full Text PDFBMC Med Educ
January 2025
Medical Education Department, Education Development Center, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Aim: The present study aimed to explore the unprofessional behavior of educators, senior students, and peers in the education process of dental and oral health services.
Method: This qualitative study employed a conventional content analysis approach. The undergraduate students (n = 21) were recruited to participate in the study through purposive sampling.
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