AIMC Topic: Aged

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Diagnosing brain tumours by routine blood tests using machine learning.

Scientific reports
Routine blood test results are assumed to contain much more information than is usually recognised even by the most experienced clinicians. Using routine blood tests from 15,176 neurological patients we built a machine learning predictive model for t...

A Dual-Modal Attention-Enhanced Deep Learning Network for Quantification of Parkinson's Disease Characteristics.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
It is well known that most patients with Parkinson's disease (PD) have different degree of movement disorders, such as shuffling, festination and akinetic episodes, which could degenerate the life quality of PD patients. Therefore, it is very useful ...

Classification of Cancer at Prostate MRI: Deep Learning versus Clinical PI-RADS Assessment.

Radiology
Background Men suspected of having clinically significant prostate cancer (sPC) increasingly undergo prostate MRI. The potential of deep learning to provide diagnostic support for human interpretation requires further evaluation. Purpose To compare t...

Physiological responses and perceived exertion during robot-assisted treadmill walking in non-ambulatory stroke survivors.

Disability and rehabilitation
PURPOSE: To examine physiological responses and perceived exertion during robot-assisted treadmill walking in non-ambulatory stroke survivors; compare these outcomes with aerobic exercise recommendations; and investigate the effect of robotic assista...

Attenuation correction using 3D deep convolutional neural network for brain 18F-FDG PET/MR: Comparison with Atlas, ZTE and CT based attenuation correction.

PloS one
One of the main technical challenges of PET/MRI is to achieve an accurate PET attenuation correction (AC) estimation. In current systems, AC is accomplished by generating an MRI-based surrogate computed tomography (CT) from which AC-maps are derived....

A network underlying human higher-order motor control: Insights from machine learning-based lesion-behaviour mapping in apraxia of pantomime.

Cortex; a journal devoted to the study of the nervous system and behavior
Neurological patients with apraxia of pantomime provide us with a unique opportunity to study the neural correlates of higher-order motor function. Previous studies using lesion-behaviour mapping methods led to inconsistent anatomical results, report...

Bag of Samplings for computer-assisted Parkinson's disease diagnosis based on Recurrent Neural Networks.

Computers in biology and medicine
Parkinson's Disease (PD) is a clinical syndrome that affects millions of people worldwide. Although considered as a non-lethal disease, PD shortens the life expectancy of the patients. Many studies have been dedicated to evaluating methods for early-...

Real-time artificial intelligence for detection of upper gastrointestinal cancer by endoscopy: a multicentre, case-control, diagnostic study.

The Lancet. Oncology
BACKGROUND: Upper gastrointestinal cancers (including oesophageal cancer and gastric cancer) are the most common cancers worldwide. Artificial intelligence platforms using deep learning algorithms have made remarkable progress in medical imaging but ...