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Deep learning-assisted diagnosis of benign and malignant parotid tumors based on ultrasound: a retrospective study.
BMC cancer
Apr 23, 2024
BACKGROUND: To develop a deep learning(DL) model utilizing ultrasound images, and evaluate its efficacy in distinguishing between benign and malignant parotid tumors (PTs), as well as its practicality in assisting clinicians with accurate diagnosis.
An explainable machine learning framework for predicting the risk of buprenorphine treatment discontinuation for opioid use disorder among commercially insured individuals.
Computers in biology and medicine
Apr 22, 2024
OBJECTIVES: Buprenorphine is an effective evidence-based medication for opioid use disorder (OUD). Yet premature discontinuation undermines treatment effectiveness, increasing the risk of mortality and overdose. We developed and evaluated a machine l...
Developing RPC-Net: Leveraging High-Density Electromyography and Machine Learning for Improved Hand Position Estimation.
IEEE transactions on bio-medical engineering
Apr 22, 2024
OBJECTIVE: The purpose of this study was to develop and evaluate the performance of RPC-Net (Recursive Prosthetic Control Network), a novel method using simple neural network architectures to translate electromyographic activity into hand position wi...
Perceptions and attitudes of dental students and dentists in South Korea toward artificial intelligence: a subgroup analysis based on professional seniority.
BMC medical education
Apr 22, 2024
BACKGROUND: This study explored dental students' and dentists' perceptions and attitudes toward artificial intelligence (AI) and analyzed differences according to professional seniority.
An ensemble model for predicting dispositions of emergency department patients.
BMC medical informatics and decision making
Apr 22, 2024
OBJECTIVE: The healthcare challenge driven by an aging population and rising demand is one of the most pressing issues leading to emergency department (ED) overcrowding. An emerging solution lies in machine learning's potential to predict ED disposit...
Classification of mental workload using brain connectivity and machine learning on electroencephalogram data.
Scientific reports
Apr 21, 2024
Mental workload refers to the cognitive effort required to perform tasks, and it is an important factor in various fields, including system design, clinical medicine, and industrial applications. In this paper, we propose innovative methods to assess...
Application of Artificial Intelligence to Automate the Reconstruction of Muscle Cross-Sectional Area Obtained by Ultrasound.
Medicine and science in sports and exercise
Apr 19, 2024
PURPOSE: Manual reconstruction (MR) of the vastus lateralis (VL) muscle cross-sectional area (CSA) from sequential ultrasound (US) images is accessible, is reproducible, and has concurrent validity with magnetic resonance imaging. However, this techn...
A single-joint multi-task motor imagery EEG signal recognition method based on Empirical Wavelet and Multi-Kernel Extreme Learning Machine.
Journal of neuroscience methods
Apr 19, 2024
BACKGROUND: In the pursuit of finer Brain-Computer Interface commands, research focus has shifted towards classifying EEG signals for multiple tasks. While single-joint multitasking motor imagery provides support, distinguishing between EEG signals f...
A neurofunctional signature of subjective disgust generalizes to oral distaste and socio-moral contexts.
Nature human behaviour
Apr 19, 2024
While disgust originates in the hard-wired mammalian distaste response, the conscious experience of disgust in humans strongly depends on subjective appraisal and may even extend to socio-moral contexts. Here, in a series of studies, we combined func...
Interactive effects of users' openness and robot reliability on trust: evidence from psychological intentions, task performance, visual behaviours, and cerebral activations.
Ergonomics
Apr 18, 2024
Although trust plays a vital role in human-robot interaction, there is currently a dearth of literature examining the effect of users' openness personality on trust in actual interaction. This study aims to investigate the interaction effects of user...
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