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Portable Ultrasound Bladder Volume Measurement Over Entire Volume Range Using a Deep Learning Artificial Intelligence Model in a Selected Cohort: A Proof of Principle Study.

Neurourology and urodynamics
OBJECTIVE: We aimed to prospectively investigate whether bladder volume measured using deep learning artificial intelligence (AI) algorithms (AI-BV) is more accurate than that measured using conventional methods (C-BV) if using a portable ultrasound ...

The impact of clinical history on the predictive performance of machine learning and deep learning models for renal complications of diabetes.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Diabetes is a chronic disease characterised by a high risk of developing diabetic nephropathy. The early identification of individuals at heightened risk of such complications or their exacerbation can be crucial to set a co...

Application of Quantitative CT and Machine Learning in the Evaluation and Diagnosis of Polymyositis/Dermatomyositis-Associated Interstitial Lung Disease.

Academic radiology
RATIONALE AND OBJECTIVES: To investigate lung changes in patients with polymyositis/dermatomyositis-associated interstitial lung disease (PM/DM-ILD) using quantitative CT and to construct a diagnostic model to evaluate the application of quantitative...

Diagnosis of thyroid cartilage invasion by laryngeal and hypopharyngeal cancers based on CT with deep learning.

European journal of radiology
OBJECTIVES: To develop a convolutional neural network (CNN) model to diagnose thyroid cartilage invasion by laryngeal and hypopharyngeal cancers observed on computed tomography (CT) images and evaluate the model's diagnostic performance.

Perception and sentiment analysis of palliative care in Chinese social media: Qualitative studies based on machine learning.

Social science & medicine (1982)
BACKGROUND: Traditional Chinese culture makes death a sensitive and taboo topic, leading patients and family members to refuse to choose palliative care.

Prediction of operation time in percutaneous nephrolithotomy (PCNL) patients: A machine learning approach.

Urologia
PURPOSE: To investigate the factors influencing the length of percutaneous nephrolithotomy (PCNL) procedures and identify predictive variables for operation time using machine learning models.

Evaluating prediction of short-term tolerability of five type 2 diabetes drug classes using routine clinical features: UK population-based study.

Diabetes, obesity & metabolism
AIMS: A precision medicine approach in type 2 diabetes (T2D) needs to consider potential treatment risks alongside established benefits for glycaemic and cardiometabolic outcomes. Considering five major T2D drug classes, we aimed to describe variatio...

Development and Validation of Ultrasound Hemodynamic-based Prediction Models for Acute Kidney Injury After Renal Transplantation.

Academic radiology
RATIONALE AND OBJECTIVES: Acute kidney injury (AKI) post-renal transplantation often has a poor prognosis. This study aimed to identify patients with elevated risks of AKI after kidney transplantation.

Blood immuno-metabolic biomarker signatures of depression and affective symptoms in young adults.

Brain, behavior, and immunity
BACKGROUND: Depression is associated with alterations in immuno-metabolic biomarkers, but it remains unclear whether these alterations are limited to specific markers, and whether there are subtypes of depression and depressive symptoms which are ass...

The interaction of UBR4, LRP1, and OPHN1 in refractory epilepsy: Drosophila model to investigate the oligogenic effect on epilepsy.

Neurobiology of disease
Refractory epilepsy is an intractable neurological disorder that can be associated with oligogenic/polygenic etiologies. Through trio-based whole-exome sequencing analysis, we identified a clinical case of refractory epilepsy with three candidate gen...