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Application Value of a Machine Learning Model in Predicting Mild Depression Associated with Migraine without Aura.

British journal of hospital medicine (London, England : 2005)
To investigate the application value of a machine learning model in predicting mild depression associated with migraine without aura (MwoA). 178 patients with MwoA admitted to the Department of Neurology of the First Affiliated Hospital of Anhui Un...

Surface and deep learning: a blended learning approach in preclinical years of medical school.

BMC medical education
BACKGROUND: Significant challenges are arising around how to best enable peer communities, broaden educational reach, and innovate in pedagogy. While digital education can address these challenges, digital elements alone do not guarantee effective le...

Deep radiomics-based prognostic prediction of oral cancer using optical coherence tomography.

BMC oral health
BACKGROUND: This study aims to evaluate the integration of optical coherence tomography (OCT) and peripheral blood immune indicators for predicting oral cancer prognosis by artificial intelligence.

Machine learning-based prediction of the risk of moderate-to-severe catheter-related bladder discomfort in general anaesthesia patients: a prospective cohort study.

BMC anesthesiology
BACKGROUND: Catheter-related bladder discomfort (CRBD) commonly occurs in patients who have indwelling urinary catheters while under general anesthesia. And moderate-to-severe CRBD can lead to significant adverse events and negatively impact patient ...

Identifying severe community-acquired pneumonia using radiomics and clinical data: a machine learning approach.

Scientific reports
Evaluating Community-Acquired Pneumonia (CAP) is crucial for determining appropriate treatment methods. In this study, we established a machine learning model using radiomics and clinical features to rapidly and accurately identify Severe Community-A...

Investigating Older Adults' Use of a Socially Assistive Robot via Time Series Clustering and User Profiling: Descriptive Analysis Study.

JMIR formative research
BACKGROUND: The aging population and the shortage of geriatric care workers are major global concerns. Socially assistive robots (SARs) have the potential to address these issues, but developing SARs for various types of users is still in its infancy...

Machine learning-based early prediction of growth and morphological traits at yearling age in pure and hybrid goat offspring.

Tropical animal health and production
The purpose of this study was to evaluate the performance of various prediction models in estimating the growth and morphological traits of pure Hair, Alpine × Hair F (AHF), and Saanen × Hair F (SHF) hybrid offspring at yearling age by employing earl...

The potential benefit of artificial intelligence regarding clinical decision-making in the treatment of wrist trauma patients.

Journal of orthopaedic surgery and research
PURPOSE: The implementation of artificial intelligence (AI) in health care is gaining popularity. Many publications describe powerful AI-enabled algorithms. Yet there's only scarce evidence for measurable value in terms of patient outcomes, clinical ...

OxcarNet: sinc convolutional network with temporal and channel attention for prediction of oxcarbazepine monotherapy responses in patients with newly diagnosed epilepsy.

Journal of neural engineering
Monotherapy with antiepileptic drugs (AEDs) is the preferred strategy for the initial treatment of epilepsy. However, an inadequate response to the initially prescribed AED is a significant indicator of a poor long-term prognosis, emphasizing the imp...

What explains adolescents' physical activity and sports participation during the COVID-19 pandemic? - an interpretable machine learning approach.

Journal of sports sciences
Adolescents' physical activity (PA) and sports participation declined due to the COVID-19 pandemic. This study aimed to determine the critical socio-ecological factors for PA and sports participation using a machine learning approach. We did a cross-...