AIMC Topic: Middle Aged

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Accuracy of automated segmentation and volumetry of acute intracerebral hemorrhage following minimally invasive surgery using a patch-based convolutional neural network in a small dataset.

Neuroradiology
PURPOSE: In cases of acute intracerebral hemorrhage (ICH) volume estimation is of prognostic and therapeutic value following minimally invasive surgery (MIS). The ABC/2 method is widely used, but suffers from inaccuracies and is time consuming. Super...

Automated Patient Registration in Magnetic Resonance Imaging Using Deep Learning-Based Height and Weight Estimation with 3D Camera: A Feasibility Study.

Academic radiology
RATIONALE AND OBJECTIVES: Accurate and efficient estimation of patient height and weight is crucial to ensure patient safety and optimize the quality of magnetic resonance imaging (MRI) procedures. Several height and weight estimation methods have be...

A Molecular Typing Method for Invasive Breast Cancer by Serum Raman Spectroscopy.

Clinical breast cancer
BACKGROUND: The incidence of breast cancer ranks highest among cancers and is exceedingly heterogeneous. Immunohistochemical staining is commonly used clinically to identify the molecular subtype for subsequent treatment and prognosis.

The Combined Effect of Robot-assisted Therapy and Activities of Daily Living Training on Upper Limb Recovery in Persons With Subacute Stroke: A Randomized Controlled Trial.

Archives of physical medicine and rehabilitation
OBJECTIVES: To evaluate the effectiveness of robot-assisted therapy (RAT) followed by activities of daily living (ADL) training in comparison with conventional rehabilitation therapy (CRT) and ADL training in individuals with subacute stroke.

Deep Learning for Automated Detection and Localization of Traumatic Abdominal Solid Organ Injuries on CT Scans.

Journal of imaging informatics in medicine
Computed tomography (CT) is the most commonly used diagnostic modality for blunt abdominal trauma (BAT), significantly influencing management approaches. Deep learning models (DLMs) have shown great promise in enhancing various aspects of clinical pr...

COPD stage detection: leveraging the auto-metric graph neural network with inspiratory and expiratory chest CT images.

Medical & biological engineering & computing
Chronic obstructive pulmonary disease (COPD) is a common lung disease that can lead to restricted airflow and respiratory problems, causing a significant health, economic, and social burden. Detecting the COPD stage can provide a timely warning for p...

Coronary artery disease evaluation during transcatheter aortic valve replacement work-up using photon-counting CT and artificial intelligence.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to evaluate the capabilities of photon-counting (PC) CT combined with artificial intelligence-derived coronary computed tomography angiography (PC-CCTA) stenosis quantification and fractional flow reserve predic...

Development of a Machine-Learning Model for Anterior Knee Pain After Total Knee Arthroplasty With Patellar Preservation Using Radiological Variables.

The Journal of arthroplasty
BACKGROUND: Anterior knee pain (AKP) following total knee arthroplasty (TKA) with patellar preservation is a common complication that significantly affects patients' quality of life. This study aimed to develop a machine-learning model to predict the...