AIMC Topic: Aged

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Automated Detection of Cerebral Microbleeds on Two-dimensional Gradient-recalled Echo T2* Weighted Images Using a Morphology Filter Bank and Convolutional Neural Network.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
PURPOSE: We present a novel algorithm for the automated detection of cerebral microbleeds (CMBs) on 2D gradient-recalled echo T2* weighted images (T2*WIs). This approach combines a morphology filter bank with a convolutional neural network (CNN) to i...

Diffusion-/perfusion-weighted imaging fusion to automatically identify stroke within 4.5 h.

European radiology
OBJECTIVES: We aimed to develop machine learning (ML) models based on diffusion- and perfusion-weighted imaging fusion (DP fusion) for identifying stroke within 4.5 h, to compare them with DWI- and/or PWI-based ML models, and to construct an automati...

Artificial intelligence predicts undiagnosed atrial fibrillation in patients with embolic stroke of undetermined source using sinus rhythm electrocardiograms.

Heart rhythm
BACKGROUND: Artificial intelligence (AI)-enabled sinus rhythm (SR) electrocardiogram (ECG) interpretation can aid in identifying undiagnosed paroxysmal atrial fibrillation (AF) in patients with embolic stroke of undetermined source (ESUS).

Machine Learning Radiomics-Based Prediction of Non-sentinel Lymph Node Metastasis in Chinese Breast Cancer Patients with 1-2 Positive Sentinel Lymph Nodes: A Multicenter Study.

Academic radiology
RATIONALE AND OBJECTIVES: This study aimed to construct a machine learning radiomics-based model using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) images to evaluate non-sentinel lymph node (NSLN) metastasis in Chinese breast cance...

Understanding COVID-19 infection among people with intellectual and developmental disabilities using machine learning.

Disability and health journal
BACKGROUND: People with intellectual and developmental disabilities (IDD) were disproportionately affected by the COVID-19 pandemic. Predicting COVID-19 infection has been difficult.

Artificial Intelligence and the Sense of Self of Older Adults: A Philosophy of Science Perspective.

The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry

Multimodal active subspace analysis for computing assessment oriented subspaces from neuroimaging data.

Journal of neuroscience methods
BACKGROUND: For successful biomarker discovery, it is essential to develop computational frameworks that summarize high-dimensional neuroimaging data in terms of involved sub-systems of the brain, while also revealing underlying heterogeneous functio...

Non-invasive assessment of response to transcatheter arterial chemoembolization for hepatocellular carcinoma with the deep neural networks-based radiomics nomogram.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Transcatheter arterial chemoembolization (TACE) is a mainstay treatment for intermediate and advanced hepatocellular carcinoma (HCC), with the potential to enhance patient survival. Preoperative prediction of postoperative response to TAC...

Comparison of an interpretable extreme gradient boosting model and an artificial neural network model for prediction of severe acute pancreatitis.

Polish archives of internal medicine
INTRODUCTION: Acute pancreatitis (AP) that progresses to persistent organ failure is referred to as severe acute pancreatitis (SAP). It is a condition associated with a relatively high mortality. A prediction model that would facilitate early recogni...