BACKGROUND: Incorrectly placed endotracheal tubes (ETTs) can lead to serious clinical harm. Studies have demonstrated the potential for artificial intelligence (AI)-led algorithms to detect ETT placement on chest X-Ray (CXR) images, however their eff...
BMC medical informatics and decision making
Jul 28, 2025
INTRODUCTION: Emergency departments (EDs) are critical for ensuring timely patient care, especially in triage, where accurate prioritisation is essential for patient safety and resource utilisation. Building on previous research, this study leverages...
OBJECTIVE: This study aimed to develop an interpretable machine learning model integrating delayed-phase contrast-enhanced CT radiomics with clinical features for noninvasive prediction of pathological grading in appendiceal pseudomyxoma peritonei (P...
PURPOSE: To predict the 1p/19q molecular status of Lower-grade glioma (LGG) patients nondestructively, this study developed a deep learning (DL) approach using radiomic to provide a potential decision aid for clinical determination of molecular strat...
BACKGROUND: Stroke is a large and increasing health challenge, leading to acquired physical disability and mortality. A rapid diagnostic assessment in the acute phase of a stroke is crucial and highly time dependent. Studies suggest that artificial i...
BMC medical informatics and decision making
Jul 28, 2025
BACKGROUND: Hyperuricemia (HUA) as a global public health challenge, although its overall epidemiological characteristics have been widely reported, its age-specific risk pattern remains controversial. This study aims to reveal the risk factors of HU...
INTRODUCTION: Robotic Exoskeleton-assisted gait training is an emerging approach in spinal cord injury (SCI) rehabilitation. This case report evaluates the effectiveness of Powered-Robotic exoskeleton-based gait training in an individual with chronic...
PURPOSE: Factors influencing missed appointments are complex and difficult to anticipate and intervene against. To optimize appointment adherence, we aimed to use personalized machine learning and big data analytics to predict the risk of and contrib...
BACKGROUND: User demographics are often hidden in social media data due to privacy concerns. However, demographic information on substance use (SU) can provide valuable insights, allowing public health policy makers to focus on specific cohorts and d...
Speech imagery is a nascent paradigm that is receiving widespread attention in current brain-computer interface (BCI) research. By collecting the electroencephalogram (EEG) data generated when imagining the pronunciation of a sentence or word in huma...
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