AIMC Topic: Machine Learning

Clear Filters Showing 9191 to 9200 of 34417 articles

Identifying neuroimaging biomarkers in major depressive disorder using machine learning algorithms and functional near-infrared spectroscopy (fNIRS) during verbal fluency task.

Journal of affective disorders
One of the most prevalent psychiatric disorders is major depressive disorder (MDD), which increases the probability of suicidal ideation or untimely demise. Abnormal frontal hemodynamic changes detected by functional near-infrared spectroscopy (fNIRS...

Artificial Intelligence, Large Language Models, and Digital Health in the Management of Alcohol-Associated Liver Disease.

Clinics in liver disease
Artificial intelligence (AI) has the potential to aid in the diagnosis and management of alcohol-associated liver disease (ALD). Machine learning algorithms can analyze medical data, such as patient records and imaging results, to identify patterns a...

Lipidomics combined with random forest machine learning algorithms to reveal freshness markers for duck eggs during storage in different rearing systems.

Poultry science
The differences in lipids in duck eggs between the 2 rearing systems during storage have not been fully studied. Herein, we propose untargeted lipidomics combined with a random forest (RF) algorithm to identify potential marker lipids based on ultra-...

Predicting ultrasound wave stimulated bone growth in bioinspired scaffolds using machine learning.

Journal of the mechanical behavior of biomedical materials
For conditions like osteoporosis, changes in bone pore geometry even when porosity is constant have been shown to correlate to increased fracture risk using techniques such as dual-energy x-ray absorptiometry (DXA) and computed tomography (CT). Addit...

Decoding micro-electrocorticographic signals by using explainable 3D convolutional neural network to predict finger movements.

Journal of neuroscience methods
BACKGROUND: Electroencephalography (EEG) and electrocorticography (ECoG) recordings have been used to decode finger movements by analyzing brain activity. Traditional methods focused on single bandpass power changes for movement decoding, utilizing m...

Immune-based Machine learning Prediction of Diagnosis and Illness State in Schizophrenia and Bipolar Disorder.

Brain, behavior, and immunity
BACKGROUND: Schizophrenia and bipolar disorder frequently face significant delay in diagnosis, leading to being missed or misdiagnosed in early stages. Both disorders have also been associated with trait and state immune abnormalities. Recent machine...

Improving the diagnostic value of lineup rejections.

Cognition
Erroneous eyewitness identification evidence is likely the leading cause of wrongful convictions. To minimize this error, scientists recommend collecting confidence. Research shows that eyewitness confidence and accuracy are strongly related when an ...

Using machine learning to explore the predictors of life satisfaction trajectories in older adults.

Applied psychology. Health and well-being
Life satisfaction is vital for older adults' well-being, impacting various life aspects. It is dynamic, necessitating nuanced approaches to capture its trajectories accurately. This study aimed to explore the diverse trajectories and predictors of li...

Computer-Aided Classification of Breast Lesions Based on US RF Time Series Using a Novel Machine Learning Approach.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: One of the most promising adjuncts for screening breast cancer is ultrasound (US) radio-frequency (RF) time series. It has the superiority of not requiring any supplementary equipment over other methods. This research aimed to propound a ...

Artificial intelligence and myocarditis-a systematic review of current applications.

Heart failure reviews
Myocarditis, marked by heart muscle inflammation, poses significant clinical challenges. This study, guided by PRISMA guidelines, explores the expanding role of artificial intelligence (AI) in myocarditis, aiming to consolidate current knowledge and ...