This article discusses the role of gestures in enhancing inhibition, working memory, and cognitive flexibility as the three components of executive functions during the processing of mathematical concepts that are metaphorically described in terms of motion events. Gestures can contribute to the process of inhibition by highlighting the relevant information and keeping the irrelevant information out of focus of attention. Gestures contribute to working memory in two ways during mathematical processing. They increase activity in the motor areas of the brain. Therefore, they may facilitate the process of understanding those mathematical concepts that are described in terms of motion event, as the motor system could play a role in the grounding and the processing of these concepts. Also, gestures can function as an external working memory and keep the visual representation of some parts of information for a short period of time in order to manipulate that information in later stages of processing. Gestures enhance cognitive flexibility by allowing us to have a spatial representation of that concept or idea for a period of time. During this time, we can shift our perspective and process that concept or idea from a variety of perspectives.
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http://dx.doi.org/10.1007/s12124-022-09694-4 | DOI Listing |
In the context of Chinese clinical texts, this paper aims to propose a deep learning algorithm based on Bidirectional Encoder Representation from Transformers (BERT) to identify privacy information and to verify the feasibility of our method for privacy protection in the Chinese clinical context. We collected and double-annotated 33,017 discharge summaries from 151 medical institutions on a municipal regional health information platform, developed a BERT-based Bidirectional Long Short-Term Memory Model (BiLSTM) and Conditional Random Field (CRF) model, and tested the performance of privacy identification on the dataset. To explore the performance of different substructures of the neural network, we created five additional baseline models and evaluated the impact of different models on performance.
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 PDFBr J Hosp Med (Lond)
January 2025
Department of Surgery & Cancer, Imperial College London, London, UK.
Predictive algorithms have myriad potential clinical decision-making implications from prognostic counselling to improving clinical trial efficiency. Large observational (or "real world") cohorts are a common data source for the development and evaluation of such tools. There is significant optimism regarding the benefits and use cases for risk-based care, but there is a notable disparity between the volume of clinical prediction models published and implementation into healthcare systems that drive and realise patient benefit.
View Article and Find Full Text PDFBr J Hosp Med (Lond)
January 2025
Department of Gastroenterology, Nantong First People's Hospital, Affiliated Hospital 2 of Nantong University, Nantong, Jiangsu, China.
Artificial intelligence (AI), with advantages such as automatic feature extraction and high data processing capacity and being unaffected by fatigue, can accurately analyze images obtained from colonoscopy, assess the quality of bowel preparation, and reduce the subjectivity of the operating physician, which may help to achieve standardization and normalization of colonoscopy. In this study, we aimed to explore the value of using an AI-driven intestinal image recognition model to evaluate intestinal preparation before colonoscopy. In this retrospective analysis, we analyzed the clinical data of 98 patients who underwent colonoscopy in Nantong First People's Hospital from May 2023 to October 2023.
View Article and Find Full Text PDFJ Integr Neurosci
January 2025
Down Syndrome Program, Division of Medical Genetics and Metabolism, Department of Pediatrics, Massachusetts General Hospital, Boston, MA 02114, USA.
Objective: To study the use of a dementia screening tool in our clinic cohort of adults with Down syndrome.
Study Design: A retrospective chart review of patients with Down syndrome was conducted to follow the use of the Adaptive Behaviour Dementia Questionnaire (ABDQ) in a dementia screening protocol. The ABDQ results for patients aged 40 years and older at a Down syndrome specialty clinic program were assessed.
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