AIMC Topic: Middle Aged

Clear Filters Showing 12201 to 12210 of 17155 articles

JOURNAL CLUB: Use of Gradient Boosting Machine Learning to Predict Patient Outcome in Acute Ischemic Stroke on the Basis of Imaging, Demographic, and Clinical Information.

AJR. American journal of roentgenology
OBJECTIVE: When treatment decisions are being made for patients with acute ischemic stroke, timely and accurate outcome prediction plays an important role. The optimal rehabilitation strategy also relies on long-term outcome predictions. The decision...

Care Personnel's Attitudes and Fears Toward Care Robots in Elderly Care: A Comparison of Data from the Care Personnel in Finland and Japan.

Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
PURPOSE: The aim of the study was to analyze and compare elderly care personnel attitudes toward care robots in Finland and Japan.

Fully Automated Delineation of Gross Tumor Volume for Head and Neck Cancer on PET-CT Using Deep Learning: A Dual-Center Study.

Contrast media & molecular imaging
PURPOSE: In this study, we proposed an automated deep learning (DL) method for head and neck cancer (HNC) gross tumor volume (GTV) contouring on positron emission tomography-computed tomography (PET-CT) images.

Deep Learning for MR Angiography: Automated Detection of Cerebral Aneurysms.

Radiology
Purpose To develop and evaluate a supportive algorithm using deep learning for detecting cerebral aneurysms at time-of-flight MR angiography to provide a second assessment of images already interpreted by radiologists. Materials and Methods MR images...

A data-driven artificial intelligence model for remote triage in the prehospital environment.

PloS one
In a mass casualty incident, the factors that determine the survival rate of injured patients are diverse, but one of the key factors is the time for triage. Additionally, the main factor that determines the time of triage is the number of medical pe...

Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification.

IEEE transactions on bio-medical engineering
Correctly identifying sleep stages is important in diagnosing and treating sleep disorders. This paper proposes a joint classification-and-prediction framework based on convolutional neural networks (CNNs) for automatic sleep staging, and, subsequent...

Analysis of tuberculosis disease through Raman spectroscopy and machine learning.

Photodiagnosis and photodynamic therapy
We present the effectiveness of Raman spectroscopy (RS) in combination with machine learning for screening and analysis of blood sera collected from tuberculosis patients. Blood samples of 60 patients have confirmed active pulmonary tuberculosis and ...

Electroencephalography-based machine learning for cognitive profiling in Parkinson's disease: Preliminary results.

Movement disorders : official journal of the Movement Disorder Society
BACKGROUND: Cognitive symptoms are common in patients with Parkinson's disease. Characterization of a patient's cognitive profile is an essential step toward the identification of predictors of cognitive worsening.

Machine learning for diagnostic ultrasound of triple-negative breast cancer.

Breast cancer research and treatment
PURPOSE: Early diagnosis of triple-negative (TN) breast cancer is important due to its aggressive biological characteristics, poor clinical outcomes, and limited options for therapy. The goal of this study is to evaluate the potential of machine lear...

Comparisons of Pressure-controlled Ventilation with Volume Guarantee and Volume-controlled 1:1 Equal Ratio Ventilation on Oxygenation and Respiratory Mechanics during Robot-assisted Laparoscopic Radical Prostatectomy: a Randomized-controlled Trial.

International journal of medical sciences
During robot-assisted laparoscopic radical prostatectomy (RALP), steep Trendelenburg position and carbon dioxide pneumoperitoneum are inevitable for surgical exposure, both of which can impair cardiopulmonary function. This study was aimed to compar...