AIMC Topic: Aged

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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.

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...

Detection of Early-Stage Colorectal Cancer Using Cell-Free oncRNA Biomarkers and Artificial Intelligence.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Colorectal cancer is the second leading cause of cancer-related deaths worldwide, and early detection significantly improves treatment outcomes, but existing blood-based tests often have limited sensitivity in early-stage disease. We develop...

Development and Validation of a Machine Learning-Based Predictive Model for Postoperative Frailty in Patients with Non-Small Cell Lung Cancer and Its Relation to Early Recovery.

Annals of surgical oncology
PURPOSE: This study was designed to evaluate the postoperative frailty status of patients with non-small cell lung cancer, identify influencing factors, establish a machine learning-based prediction model, and explore the correlation between frailty ...

Breast cancer neoadjuvant therapy outcome prediction based on clinical patient and tumor features: A cross-sectional study.

Current problems in cancer
INTRODUCTION: Breast cancer is the most common malignant disease in the female population and one of the most common diseases in developed countries. Many factors which may impact the development and outcome of this complex disease have been investig...

Development of patient-specific apparent blood viscosity predictive models for computational fluid dynamics analysis of intracranial aneurysms with machine learning approaches.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: A model to predict patient-specific apparent viscosity as a computational condition in computational fluid dynamics (CFD) analysis, which is used in research on intracranial aneurysms, is important. The purpose of this stud...