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Utility of Thin-slice Single-shot T2-weighted MR Imaging with Deep Learning Reconstruction as a Protocol for Evaluating Pancreatic Cystic Lesions.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
PURPOSE: To assess the effects of industry-developed deep learning reconstruction with super resolution (DLR-SR) on single-shot turbo spin-echo (SshTSE) images with thickness of 2 mm with DLR (SshTSE) relative to those of images with a thickness of 5...

Machine learning approaches for predicting heart failure readmissions.

Postgraduate medical journal
PURPOSE: This study aims to develop and evaluate machine learning (ML) models to predict the likelihood of hospital readmission within 30 days after discharge for patients with heart failure (HF). The goal is to compare the predictive accuracy of ML ...

Stereotactic Radiation Therapy or Protons for Uveal Melanoma Patients? An Artificial Intelligence (AI)-Based Clinical Treatment Decision-Making Tool Predicting Doses To Radiation Therapy Constraints.

International journal of radiation oncology, biology, physics
PURPOSE: For ocular melanoma, selecting between stereotactic radiation therapy (SRT) and protons requires a lengthy plan comparison process. The purpose of this brief report is to describe an artificial intelligence (AI) decision-making tool to predi...

Comparative cytokine signatures and cognitive deficits in early-onset schizophrenia and adolescent major depression: Toward refined diagnostic classification frameworks.

Journal of affective disorders
BACKGROUND: This study analyzed plasma cytokine patterns in individuals with schizophrenia (SCZ), major depressive disorder (MDD), and healthy controls, explored the link between cytokine levels and cognitive function, and created machine learning mo...

From quality of life to sleep quality in Chinese college students: stress and anxiety as sequential mediators with nonlinear effects via machine learning.

Journal of affective disorders
OBJECT: This study examines how quality of life is associated with sleep quality among Chinese university students through sequential mediation by perceived stress and sleep anxiety, using machine learning to uncover nonlinear effects.

Machine learning identifies prominent risk factors for depressive symptoms among Chinese children and adolescents.

Journal of affective disorders
BACKGROUND: Identifying key risk factors for depressive symptoms in children and adolescents is crucial for prevention. However, few studies have explored this topic. This study aimed to examine the prevalence of depressive symptoms in Chinese childr...

Enhancing differentiation between unipolar and bipolar depression through integration of machine learning and electroencephalogram analysis.

Journal of affective disorders
To enhance the differentiation between unipolar depression (UPD) and bipolar depression (BPD), this study integrates machine learning and deep learning models with electroencephalography (EEG) data and clinical features. Utilizing Python for data pre...

Discovering the metabolic pathway of liver disease by breath mass spectrometry combined with machine learning.

Journal of pharmaceutical and biomedical analysis
On account of the low concentration and complex background, most methods for detecting VOCs in exhaled breath samples required preconcentration prior to instrumental analysis. In the current study, a simple and rapid method is developed for analyzing...

Prognostic factors and prediction model for facial scar improvement in laser-treated patients: A machine learning-based retrospective cohort study.

Medicine
The face, being central and exposed, is highly susceptible to trauma and subsequent scar formation. Laser therapy is a common and effective treatment method for facial scars. However, treatment outcomes vary substantially. Consequently, we aimed to i...