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Lower Limb Motion Recognition Based on sEMG and CNN-TL Fusion Model.
Sensors (Basel, Switzerland)
Nov 4, 2024
To enhance the classification accuracy of lower limb movements, a fusion recognition model integrating a surface electromyography (sEMG)-based convolutional neural network, transformer encoder, and long short-term memory network (CNN-Transformer-LSTM...
Using machine learning to classify temporomandibular disorders: a proof of concept.
Journal of applied oral science : revista FOB
Nov 4, 2024
BACKGROUND: the escalating influx of patients with temporomandibular disorders and the challenges associated with accurate diagnosis by non-specialized dental practitioners underscore the integration of artificial intelligence into the diagnostic pro...
Assessing nursing students' e-health literacy and foresights to global health challenges during COVID-19 restrictions: A cross-sectional study with a machine learning approach.
Nurse education in practice
Nov 2, 2024
AIM: This study aims to assess the e-health literacy and foresights to global health challenges of nursing students during the COVID19 restrictions.
Using interpretable machine learning methods to identify the relative importance of lifestyle factors for overweight and obesity in adults: pooled evidence from CHNS and NHANES.
BMC public health
Nov 1, 2024
BACKGROUND: Overweight and obesity pose a huge burden on individuals and society. While the relationship between lifestyle factors and overweight and obesity is well-established, the relative contribution of specific lifestyle factors remains unclear...
Relationship Between Individual Innovativeness Levels and Attitudes Toward Artificial Intelligence Among Nursing and Midwifery Students.
Computers, informatics, nursing : CIN
Nov 1, 2024
The aim of this study is to explore the connection between individual innovativeness levels and attitudes toward artificial intelligence among nursing and midwifery students. Data were collected from 500 nursing and midwifery students studying at a u...
Machine learning-based estimation of respiratory fluctuations in a healthy adult population using resting state BOLD fMRI and head motion parameters.
Magnetic resonance in medicine
Oct 31, 2024
PURPOSE: External physiological monitoring is the primary approach to measure and remove effects of low-frequency respiratory variation from BOLD-fMRI signals. However, the acquisition of clean external respiratory data during fMRI is not always poss...
Application of machine learning in predicting health perception through military personnel's sense of empowerment.
Applied psychology. Health and well-being
Oct 31, 2024
The promotion of health and provision of care services for new recruits are issues of constant concern for military leaders and healthcare providers, as they are crucial to maintaining and operating military forces. The enhancement of military person...
Pharmacy students' perception and knowledge of chat-based artificial intelligence tools at a Nigerian University.
BMC medical education
Oct 31, 2024
BACKGROUND: Chat-based Artificial Intelligence (AI) tools, such as ChatGPT, are becoming integral to various aspects of pharmacy education. However, their integration into the curriculum faces challenges due to students' varying levels of knowledge a...
Medical students and house officers' perception, attitude and potential barriers towards artificial intelligence in Egypt, cross sectional survey.
BMC medical education
Oct 31, 2024
BACKGROUND: Artificial intelligence (AI) is one of the sectors of medical research that is expanding the fastest right now in healthcare. AI has rapidly advanced in the field of medicine, helping to treat a variety of illnesses and reducing the numbe...
Detecting the impact of diagnostic procedures in Pap-positive women on anxiety using artificial neural networks.
PloS one
Oct 31, 2024
INTRODUCTION: Women who receive a result of an abnormal Papanicolaou (Pap) smear can fail to participate in follow up procedures, and this is often due to anxiety. This study aimed to apply artificial neural networks (ANN) in prediction of anxiety in...
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