AIMC Topic: Middle Aged

Clear Filters Showing 9391 to 9400 of 17155 articles

Predictive modeling for peri-implantitis by using machine learning techniques.

Scientific reports
The purpose of this retrospective cohort study was to create a model for predicting the onset of peri-implantitis by using machine learning methods and to clarify interactions between risk indicators. This study evaluated 254 implants, 127 with and 1...

Automatic detect lung node with deep learning in segmentation and imbalance data labeling.

Scientific reports
In this study, a novel method with the U-Net-based network architecture, 2D U-Net, is employed to segment the position of lung nodules, which are an early symptom of lung cancer and have a high probability of becoming a carcinoma, especially when a l...

Toward understanding COVID-19 pneumonia: a deep-learning-based approach for severity analysis and monitoring the disease.

Scientific reports
We report a new approach using artificial intelligence (AI) to study and classify the severity of COVID-19 using 1208 chest X-rays (CXRs) of 396 COVID-19 patients obtained through the course of the disease at Emory Healthcare affiliated hospitals (At...

Explaining deep neural networks for knowledge discovery in electrocardiogram analysis.

Scientific reports
Deep learning-based tools may annotate and interpret medical data more quickly, consistently, and accurately than medical doctors. However, as medical doctors are ultimately responsible for clinical decision-making, any deep learning-based prediction...

Developing a short-term prediction model for asthma exacerbations from Swedish primary care patients' data using machine learning - Based on the ARCTIC study.

Respiratory medicine
OBJECTIVE: The ability to predict impending asthma exacerbations may allow better utilization of healthcare resources, prevention of hospitalization and improve patient outcomes. We aimed to develop models using machine learning to predict risk of ex...

Cortical Thickness from MRI to Predict Conversion from Mild Cognitive Impairment to Dementia in Parkinson Disease: A Machine Learning-based Model.

Radiology
Background Group comparison results associating cortical thinning and Parkinson disease (PD) dementia (PDD) are limited in their application to clinical settings. Purpose To investigate whether cortical thickness from MRI can help predict conversion ...

Robot-Assisted Stereotactic Shunting as a Novel Treatment for Pontine Glioependymal Cysts.

Journal of neurological surgery. Part A, Central European neurosurgery
In this case report, the authors describe the first case of a glioependymal cyst of the brainstem managed by robot-assisted, stereotactic, cysto-ventricular shunting. Glioependymal cysts are rare congenital cystic lesions that are thought to form by ...

Using deep learning convolutional neural networks to automatically perform cerebral aqueduct CSF flow analysis.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Since the development of phase-contrast magnetic resonance imaging (PC-MRI), quantification of cerebrospinal fluid (CSF) flow across the cerebral aqueduct has been utilized for diagnosis of conditions such as normal pressure hydrocephalus (NPH). This...

Predicting optimal deep brain stimulation parameters for Parkinson's disease using functional MRI and machine learning.

Nature communications
Commonly used for Parkinson's disease (PD), deep brain stimulation (DBS) produces marked clinical benefits when optimized. However, assessing the large number of possible stimulation settings (i.e., programming) requires numerous clinic visits. Here,...