Artificial intelligence (AI) was once considered avant-garde. However, AI permeates every industry today, impacting work and home lives in many ways. While AI-driven diagnostic and therapeutic applications already exist in medicine, a chasm remains between the potential of AI and its clinical applications. This article reviews the status of AI-powered ultrasound (US) applications in anaesthesiology and perioperative medicine. A literature search was performed for studies examining AI applications in perioperative US. AI applications for echocardiography and regional anaesthesia are the most robust and well-developed. While applications are available for lung imaging and vascular access, AI programs for airway and gastric US imaging solutions have yet to be available. Legal and ethical challenges associated with AI applications need to be addressed and resolved over time. AI applications are beneficial in the context of education and training. While low-resource settings may benefit from AI, the financial burden is a considerable limiting factor.
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http://dx.doi.org/10.4103/ija.ija_578_24 | DOI Listing |
BMC Public Health
December 2024
Fourth Kindergarten of Guangdong Military Region, Guangzhou, China.
Background: Early childhood is a sensitive period for the development of agility and balance quality. Currently, children's agility and balance quality are gradually declining, and the pathways for enhancing these qualities are limited. In light of this, the study adopts a set theory perspective to explore the configurational pathways through which subsystems of gross motor skills can promote children's agility and balance quality.
View Article and Find Full Text PDFBMC Bioinformatics
December 2024
College of Computer Science and Technology, Inner Mongolia Minzu University, Tongliao, 028000, China.
As a heterogeneous disease, prostate cancer (PCa) exhibits diverse clinical and biological features, which pose significant challenges for early diagnosis and treatment. Metabolomics offers promising new approaches for early diagnosis, treatment, and prognosis of PCa. However, metabolomics data are characterized by high dimensionality, noise, variability, and small sample sizes, presenting substantial challenges for classification.
View Article and Find Full Text PDFBMC Health Serv Res
December 2024
Health Services Research and Development Center, University of Tsukuba, Ibaraki, Japan.
Background: Community- and evidence-based approaches are essential for improving dental public health. We evaluated the effectiveness of sending vouchers in a community-based oral screening program to encourage dental visits and improve oral health among adults.
Methods: We analyzed the data from April 2014 to March 2019 obtained from administrative claims and screening program databases in Tsukuba City, Japan.
BMC Med Res Methodol
December 2024
School of Mathematical & Statistical Sciences, University of Texas Rio Grande Valley, One West University Boulevard, Brownsville, TX, 78520, USA.
Background: Missing observations within the univariate time series are common in real-life and cause analytical problems in the flow of the analysis. Imputation of missing values is an inevitable step in every incomplete univariate time series. Most of the existing studies focus on comparing the distributions of imputed data.
View Article and Find Full Text PDFCurr Urol Rep
December 2024
Department of Urology, Lahey Hospital and Medical Center, MA, Burlington, USA.
Purpose Of Review: Artificial Intelligence (AI) has produced a significant impact across various industries, including healthcare. In the outpatient clinic setting, AI offers promising improvements in efficiency through Chatbots, streamlined medical documentation, and personalized patient education materials. On the billing side, AI technologies hold potential for optimizing the selection of appropriate billing codes, automating prior authorizations, and enhancing healthcare fraud detection.
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