AIMC Topic: Aged

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Artificial intelligence quantified tumour-stroma ratio is an independent predictor for overall survival in resectable colorectal cancer.

EBioMedicine
BACKGROUND: An artificial intelligence method could accelerate the clinical implementation of tumour-stroma ratio (TSR), which has prognostic relevance in colorectal cancer (CRC). We, therefore, developed a deep learning model for the fully automated...

Data mining of human plasma proteins generates a multitude of highly predictive aging clocks that reflect different aspects of aging.

Aging cell
We previously identified 529 proteins that had been reported by multiple different studies to change their expression level with age in human plasma. In the present study, we measured the q-value and age coefficient of these proteins in a plasma prot...

[Autonomous assitive robots for older people at home: An exploratory study : "He is always there for me-and I for him too"].

Zeitschrift fur Gerontologie und Geriatrie
The use of autonomous assistive robots in the domestic environment of old people and the possible effects on the quality of life is a relatively new field of research. Given the relatively limited technical robustness of these robots, autonomous assi...

Facial erythema detects diabetic neuropathy using the fusion of machine learning, random matrix theory and self organized criticality.

Scientific reports
Rubeosis faciei diabeticorum, caused by microangiopathy and characterized by a chronic facial erythema, is associated with diabetic neuropathy. In clinical practice, facial erythema of patients with diabetes is evaluated based on subjective observati...

Activity-based training with the Myosuit: a safety and feasibility study across diverse gait disorders.

Journal of neuroengineering and rehabilitation
BACKGROUND: Physical activity is a recommended part of treatment for numerous neurological and neuromuscular disorders. Yet, many individuals with limited mobility are not able to meet the recommended activity levels. Lightweight, wearable robots lik...

Automated Segmentation of Retinal Fluid Volumes From Structural and Angiographic Optical Coherence Tomography Using Deep Learning.

Translational vision science & technology
PURPOSE: We proposed a deep convolutional neural network (CNN), named Retinal Fluid Segmentation Network (ReF-Net), to segment retinal fluid in diabetic macular edema (DME) in optical coherence tomography (OCT) volumes.

Characterization and wearability evaluation of a fully portable wrist exoskeleton for unsupervised training after stroke.

Journal of neuroengineering and rehabilitation
BACKGROUND: Chronic hand and wrist impairment are frequently present following stroke and severely limit independence in everyday life. The wrist orientates and stabilizes the hand before and during grasping, and is therefore of critical importance i...

External Validation of the Long Short-Term Memory Artificial Neural Network-Based SCaP Survival Calculator for Prediction of Prostate Cancer Survival.

Cancer research and treatment
PURPOSE: Decision-making for treatment of newly diagnosed prostate cancer (PCa) is complex due to the multiple initial treatment modalities available. We aimed to externally validate the SCaP (Severance Study Group of Prostate Cancer) Survival Calcul...

Prospective Validation of Vesical Imaging-Reporting and Data System Using a Next-Generation Magnetic Resonance Imaging Scanner-Is Denoising Deep Learning Reconstruction Useful?

The Journal of urology
PURPOSE: The Vesical Imaging Reporting and Data System (VI-RADS) was launched in 2018 to standardize reporting of magnetic resonance imaging for bladder cancer. This study aimed to prospectively validate VI-RADS using a next-generation magnetic reson...

Machine learning-based FDG PET-CT radiomics for outcome prediction in larynx and hypopharynx squamous cell carcinoma.

Clinical radiology
AIM: To determine whether machine learning-based radiomic feature analysis of baseline integrated 2-[F]-fluoro-2-deoxy-d-glucose (FDG) positron-emission tomography (PET) computed tomography (CT) predicts disease progression in patients with locally a...